
ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

               MotifID: 'IL_00225.13'
             Signature: {'cWW-L-cWW'  ''}
                 NumNT: 5
          NumBasepairs: 2
            Structured: 1
             NumStacks: 3
                NumBPh: 0
                 NumBR: 0
          NumInstances: 49
              Truncate: 4
              NumFixed: 16
              OwnScore: [-3.4465 -3.2245 -3.3938 -3.2245 -3.6472 -3.6472 -3.2245 -3.2631 -5.2582 -3.9556 -5.2582 -3.9556 -3.2245 -3.2245 … ]
           OwnSequence: {1×49 cell}
          DeficitCoeff: 1
         CoreEditCoeff: 3
       SequenceLengths: [5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5]
    MeanSequenceLength: 5
       DeficitEditData: [4929×2 double]

49 sequences from 3D structures
Using 4929 random sequences, 0 from an alignment, and 49 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group   1, IL_00225.13 has acceptance rules AlignmentScore >= -23.1718, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  12.6718
TP   100.00%, TN    87.82%, min    87.82%,  49 3D sequences,     0 alignment sequences, 4565 random sequences,  556 random matches,  5 NTs, cWW-L-cWW
Sensitivity 100.00%, Specificity  87.82%, Minimum  87.82% using method 11
Number of false positives with core edit > 0 is 556
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11
Motif index 12
Motif index 13
Motif index 14
Motif index 15
Motif index 16
Motif index 17
Motif index 18
Motif index 19
Motif index 20
Motif index 21
Motif index 22
Motif index 23
Motif index 24
Motif index 25
Motif index 26
Motif index 27
Motif index 28
Motif index 29
Motif index 30
Motif index 31
Motif index 32
Motif index 33
Motif index 34
Motif index 35
Motif index 36
Motif index 37
Motif index 38
Motif index 39
Motif index 40
Motif index 41
Motif index 42
Motif index 43
Motif index 44
Motif index 45
Motif index 46
Motif index 47
Motif index 48
Motif index 49


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_00555.1'
                     Signature: {'cWW-cWS-cWW-L-R'  ''}
                         NumNT: 6
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 2
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 5
                      NumFixed: 22
                      OwnScore: [-7.3179 -7.3179]
                   OwnSequence: {'AUGAAGC*GGGU'  'AUGAAGC*GGGU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11]
            MeanSequenceLength: 11
               DeficitEditData: [10349×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 10349 random sequences, 0 from an alignment, and 2 from 3D structures
Group   2, IL_00555.1  has acceptance rules AlignmentScore >= -27.3179, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.3966
TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 10349 random sequences,  414 random matches,  6 NTs, cWW-cWS-cWW-L-R
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 414
1 * Deficit + 3 * Core Edit <= 17.0787
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_00881.1'
                     Signature: {'cWW-L-cWW-L'  ''}
                         NumNT: 6
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 5
                      NumFixed: 20
                      OwnScore: [-5.7200 -4.7734]
                   OwnSequence: {'CACAA*UG'  'CAAG*UG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 6]
            MeanSequenceLength: 6.5000
               DeficitEditData: [11767×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 11767 random sequences, 0 from an alignment, and 2 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group   3, IL_00881.1  has acceptance rules AlignmentScore >= -24.7734, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  14.2734
TP   100.00%, TN    90.90%, min    90.90%,   2 3D sequences,     0 alignment sequences, 11656 random sequences, 1061 random matches,  6 NTs, cWW-L-cWW-L
Sensitivity 100.00%, Specificity  90.90%, Minimum  90.90% using method 11
Number of false positives with core edit > 0 is 1061
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_00981.1'
                     Signature: {'cWW-tWH-tHH-tHS-cWW'  ''}
                         NumNT: 10
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 3
                         NumBR: 2
                  NumInstances: 2
                      Truncate: 6
                      NumFixed: 18
                      OwnScore: [-4.3867 -4.3867]
                   OwnSequence: {'UUAAC*GGAAGA'  'UUAAC*GGAAGA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11]
            MeanSequenceLength: 11
               DeficitEditData: [4919×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 4919 random sequences, 0 from an alignment, and 2 from 3D structures
Group   4, IL_00981.1  has acceptance rules AlignmentScore >= -24.3867, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  21.7909
TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 4919 random sequences,  197 random matches, 10 NTs, cWW-tWH-tHH-tHS-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 197
1 * Deficit + 3 * Core Edit <= 17.4042
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_01038.1'
                     Signature: {'cWW-tWH-L-R-tHS-cWW'  ''}
                         NumNT: 10
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 6
                      NumFixed: 24
                      OwnScore: -6.8083
                   OwnSequence: {'GCAAG*UGAAAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 11
            MeanSequenceLength: 11
               DeficitEditData: [8202×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 8202 random sequences, 0 from an alignment, and 1 from 3D structures
Group   5, IL_01038.1  has acceptance rules AlignmentScore >= -26.8083, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  23.5459
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 8202 random sequences,  328 random matches, 10 NTs, cWW-tWH-L-R-tHS-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 328
1 * Deficit + 3 * Core Edit <= 16.7376
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_01176.1'
                     Signature: {'cWW-L-R-L-R-L-R-L-cWW'  ''}
                         NumNT: 11
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 7
                      NumFixed: 28
                      OwnScore: -9.1223
                   OwnSequence: {'CGCCUU*AAAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 11
            MeanSequenceLength: 11
               DeficitEditData: [7387×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 7387 random sequences, 0 from an alignment, and 1 from 3D structures
Group   6, IL_01176.1  has acceptance rules AlignmentScore >= -29.1223, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.2712
TP   100.00%, TN    96.01%, min    96.01%,   1 3D sequences,     0 alignment sequences, 7387 random sequences,  295 random matches, 11 NTs, cWW-L-R-L-R-L-R-L-cWW
Sensitivity 100.00%, Specificity  96.01%, Minimum  96.01% using method 6
Number of false positives with core edit > 0 is 295
1 * Deficit + 3 * Core Edit <= 16.1489
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_01488.3'
                     Signature: {'cWW-tSS-tSH-L-R-tHS-L-cWW'  ''}
                         NumNT: 12
                  NumBasepairs: 7
                    Structured: 1
                     NumStacks: 12
                        NumBPh: 3
                         NumBR: 2
                  NumInstances: 10
                      Truncate: 8
                      NumFixed: 30
                      OwnScore: [-6.3878 -6.8069 -6.5236 -9.4613 -6.7243 -8.5125 -12.4954 -6.8069 -10.8548 -6.6577]
                   OwnSequence: {1×10 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [13 13 13 13 13 13 13 13 13 13]
            MeanSequenceLength: 13
               DeficitEditData: [2627×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

10 sequences from 3D structures
Using 2627 random sequences, 0 from an alignment, and 10 from 3D structures
Group   7, IL_01488.3  has acceptance rules AlignmentScore >= -26.3878, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.7644
TP   100.00%, TN    96.00%, min    96.00%,  10 3D sequences,     0 alignment sequences, 2627 random sequences,  105 random matches, 12 NTs, cWW-tSS-tSH-L-R-tHS-L-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 105
1 * Deficit + 3 * Core Edit <= 18.3766
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_01994.1'
                     Signature: {'cWW-cWH-tHS-cWW-cSH-cWW'  ''}
                         NumNT: 8
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 3
                      Truncate: 6
                      NumFixed: 26
                      OwnScore: [-4.2234 -4.2234 -4.1444]
                   OwnSequence: {'GGACUG*CGC'  'GGUCUG*CGC'  'UGCUG*CGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 8]
            MeanSequenceLength: 8.6667
               DeficitEditData: [6514×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 6514 random sequences, 0 from an alignment, and 3 from 3D structures
Group   8, IL_01994.1  has acceptance rules AlignmentScore >= -24.1444, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  18.9778
TP   100.00%, TN    95.98%, min    95.98%,   3 3D sequences,     0 alignment sequences, 6513 random sequences,  262 random matches,  8 NTs, cWW-cWH-tHS-cWW-cSH-cWW
Sensitivity 100.00%, Specificity  95.98%, Minimum  95.98% using method 6
Number of false positives with core edit > 0 is 262
1 * Deficit + 3 * Core Edit <= 14.8334
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_02203.1'
                     Signature: {'cWW-cSW-cWW-cWW'  ''}
                         NumNT: 8
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 5
                      NumFixed: 16
                      OwnScore: -4.4173
                   OwnSequence: {'AUUG*CUGU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 8
            MeanSequenceLength: 8
               DeficitEditData: [5881×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 5881 random sequences, 0 from an alignment, and 1 from 3D structures
Group   9, IL_02203.1  has acceptance rules AlignmentScore >= -24.4173, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.5343
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 5870 random sequences,  235 random matches,  8 NTs, cWW-cSW-cWW-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 235
1 * Deficit + 3 * Core Edit <= 12.1170
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_02349.4'
                     Signature: {'cWW-tSH-tWH-cSH-tWH-tHS-cWW'  ''}
                         NumNT: 13
                  NumBasepairs: 7
                    Structured: 1
                     NumStacks: 13
                        NumBPh: 3
                         NumBR: 3
                  NumInstances: 3
                      Truncate: 8
                      NumFixed: 26
                      OwnScore: [-6.0968 -6.0968 -6.3556]
                   OwnSequence: {'GGGAGUAG*CGAGAC'  'GGGAGUAG*CGAGAC'  'GGGAGUAG*CAAGAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [14 14 14]
            MeanSequenceLength: 14
               DeficitEditData: [1482×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 1482 random sequences, 0 from an alignment, and 3 from 3D structures
Decreased cutoff from  22.1709 because the cutoff seemed overly generous
Group  10, IL_02349.4  has acceptance rules AlignmentScore >= -26.0968, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.2107
TP   100.00%, TN    97.98%, min    97.98%,   3 3D sequences,     0 alignment sequences, 1482 random sequences,   30 random matches, 13 NTs, cWW-tSH-tWH-cSH-tWH-tHS-cWW
Sensitivity 100.00%, Specificity  97.98%, Minimum  97.98% using method 8
Number of false positives with core edit > 0 is 30
1 * Deficit + 3 * Core Edit <= 20.1139
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_02555.1'
                     Signature: {'cWW-L-cWW'  ''}
                         NumNT: 5
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 2
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 9
                      Truncate: 4
                      NumFixed: 20
                      OwnScore: [-2.3022 -2.3022 -2.3022 -2.3022 -2.3022 -2.5177 -2.5177 -5.9675 -5.9105]
                   OwnSequence: {'CAAG*UG'  'CAAG*UG'  'CAAG*UG'  'CAAG*UG'  'CAAG*UG'  'UAAG*UA'  'UAAG*UA'  'CAAG*CG'  'CUAG*CG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 6 6 6 6 6 6 6]
            MeanSequenceLength: 6
               DeficitEditData: [7558×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

9 sequences from 3D structures
Using 7558 random sequences, 0 from an alignment, and 9 from 3D structures
Group  11, IL_02555.1  has acceptance rules AlignmentScore >= -22.3022, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  11.8699
TP   100.00%, TN    95.98%, min    95.98%,   9 3D sequences,     0 alignment sequences, 7368 random sequences,  296 random matches,  5 NTs, cWW-L-cWW
Sensitivity 100.00%, Specificity  95.98%, Minimum  95.98% using method 6
Number of false positives with core edit > 0 is 296
1 * Deficit + 3 * Core Edit <= 9.5677
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_03109.3'
                     Signature: {'cWW-cWS-tWH-cWW-L'  ''}
                         NumNT: 7
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 6
                      Truncate: 6
                      NumFixed: 24
                      OwnScore: [-3.4885 -3.4885 -3.7523 -4.5827 -8.1832 -6.9320]
                   OwnSequence: {'CCAAU*AG'  'CCAAU*AG'  'ACAAU*AU'  'GCAAU*AC'  'UGGCC*GG'  'UGACC*GG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 7 7 7 7 7]
            MeanSequenceLength: 7
               DeficitEditData: [3961×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

6 sequences from 3D structures
Using 3961 random sequences, 0 from an alignment, and 6 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group  12, IL_03109.3  has acceptance rules AlignmentScore >= -23.4885, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  12.9885
TP   100.00%, TN    94.79%, min    94.79%,   6 3D sequences,     0 alignment sequences, 3897 random sequences,  203 random matches,  7 NTs, cWW-cWS-tWH-cWW-L
Sensitivity 100.00%, Specificity  94.79%, Minimum  94.79% using method 11
Number of false positives with core edit > 0 is 203
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_03350.1'
                     Signature: {'cWW-tWH-cWW-L-L-cWW-L-L-L'  ''}
                         NumNT: 13
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 12
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 3
                      Truncate: 10
                      NumFixed: 30
                      OwnScore: [-7.8058 -7.2950 -7.2950]
                   OwnSequence: {'CUCCCCACC*GAGG'  'CUACCCACC*GAGG'  'CUACCCACC*GAGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [13 13 13]
            MeanSequenceLength: 13
               DeficitEditData: [695×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 695 random sequences, 0 from an alignment, and 3 from 3D structures
Decreased cutoff from  21.2035 because the cutoff seemed overly generous
Group  13, IL_03350.1  has acceptance rules AlignmentScore >= -27.2950, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  27.2950
TP   100.00%, TN    97.41%, min    97.41%,   3 3D sequences,     0 alignment sequences,  695 random sequences,   18 random matches, 13 NTs, cWW-tWH-cWW-L-L-cWW-L-L-L
Sensitivity 100.00%, Specificity  97.41%, Minimum  97.41% using method 8
Number of false positives with core edit > 0 is 18
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_04021.2'
                     Signature: {'cWW-L-R-tSH-tSH-tHS-cWW-cWW'  ''}
                         NumNT: 14
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 14
                        NumBPh: 4
                         NumBR: 5
                  NumInstances: 7
                      Truncate: 8
                      NumFixed: 28
                      OwnScore: [-6.1612 -6.1612 -6.1612 -7.5347 -6.1612 -7.5347 -7.3402]
                   OwnSequence: {1×7 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [14 14 14 14 14 14 14]
            MeanSequenceLength: 14
               DeficitEditData: [1236×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

7 sequences from 3D structures
Using 1236 random sequences, 0 from an alignment, and 7 from 3D structures
Decreased cutoff from  21.3052 because the cutoff seemed overly generous
Group  14, IL_04021.2  has acceptance rules AlignmentScore >= -26.1612, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.1612
TP   100.00%, TN    97.65%, min    97.65%,   7 3D sequences,     0 alignment sequences, 1236 random sequences,   29 random matches, 14 NTs, cWW-L-R-tSH-tSH-tHS-cWW-cWW
Sensitivity 100.00%, Specificity  97.65%, Minimum  97.65% using method 8
Number of false positives with core edit > 0 is 29
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_04073.1'
                     Signature: {'cWW-L-R-L-tSH-L-R-cWW-L-R-R-L-cWW-L'  ''}
                         NumNT: 18
                  NumBasepairs: 7
                    Structured: 1
                     NumStacks: 15
                        NumBPh: 0
                         NumBR: 2
                  NumInstances: 1
                      Truncate: 11
                      NumFixed: 46
                      OwnScore: -12.2606
                   OwnSequence: {'AUAAGGAUUGA*UCUUGAUUU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 20
            MeanSequenceLength: 20
               DeficitEditData: [6×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 6 random sequences, 0 from an alignment, and 1 from 3D structures
Group  15, IL_04073.1  has acceptance rules AlignmentScore >= -32.2606, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  37.2606
TP   100.00%, TN   100.00%, min   100.00%,   1 3D sequences,     0 alignment sequences,    6 random sequences,    0 random matches, 18 NTs, cWW-L-R-L-tSH-L-R-cWW-L-R-R-L-cWW-L
Sensitivity 100.00%, Specificity 100.00%, Minimum 100.00% using method 1
Number of false positives with core edit > 0 is 0
1 * Deficit + 3 * Core Edit <= 25.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_04307.1'
                     Signature: {'cWW-L-R-L-R-L-R-L-R-L-cWW-L-L-R'  ''}
                         NumNT: 16
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 13
                        NumBPh: 0
                         NumBR: 2
                  NumInstances: 1
                      Truncate: 11
                      NumFixed: 54
                      OwnScore: -10.2277
                   OwnSequence: {'CCAUACCUUG*CCUCAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 16
            MeanSequenceLength: 16
               DeficitEditData: [128×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 128 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  22.3156 because the cutoff seemed overly generous
Group  16, IL_04307.1  has acceptance rules AlignmentScore >= -30.2277, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  30.6404
TP   100.00%, TN    97.66%, min    97.66%,   1 3D sequences,     0 alignment sequences,  128 random sequences,    3 random matches, 16 NTs, cWW-L-R-L-R-L-R-L-R-L-cWW-L-L-R
Sensitivity 100.00%, Specificity  97.66%, Minimum  97.66% using method 8
Number of false positives with core edit > 0 is 3
1 * Deficit + 3 * Core Edit <= 20.4127
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_04332.3'
                     Signature: {'cWW-L-R-L-cWW-L-L-R-L-R-L'  ''}
                         NumNT: 13
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 2
                         NumBR: 2
                  NumInstances: 2
                      Truncate: 11
                      NumFixed: 38
                      OwnScore: [-10.3727 -8.7788]
                   OwnSequence: {'CGAAAUUCCUUG*CCUG'  'CGUAGUACCUUG*CUUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [16 16]
            MeanSequenceLength: 16
               DeficitEditData: [338×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 338 random sequences, 0 from an alignment, and 2 from 3D structures
Decreased cutoff from  23.9065 because the cutoff seemed overly generous
Group  17, IL_04332.3  has acceptance rules AlignmentScore >= -28.7788, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  31.2893
TP   100.00%, TN    97.93%, min    97.93%,   2 3D sequences,     0 alignment sequences,  338 random sequences,    7 random matches, 13 NTs, cWW-L-R-L-cWW-L-L-R-L-R-L
Sensitivity 100.00%, Specificity  97.93%, Minimum  97.93% using method 8
Number of false positives with core edit > 0 is 7
1 * Deficit + 3 * Core Edit <= 22.5105
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_04346.10'
                     Signature: {'cWW-cWW-tSH-tHH-cSH-tWH-tHS-cWW'  ''}
                         NumNT: 15
                  NumBasepairs: 8
                    Structured: 1
                     NumStacks: 20
                        NumBPh: 3
                         NumBR: 2
                  NumInstances: 15
                      Truncate: 9
                      NumFixed: 28
                      OwnScore: [-7.9350 -8.2148 -8.1689 -7.9350 -9.4156 -9.7918 -9.6575 -11.3924 -11.3924 -10.2946 -8.0879 -8.6031 … ]
                   OwnSequence: {1×15 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [15 15 15 15 15 15 15 16 16 15 15 15 15 15 15]
            MeanSequenceLength: 15.1333
               DeficitEditData: [1001×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

15 sequences from 3D structures
Using 1001 random sequences, 0 from an alignment, and 15 from 3D structures
Decreased cutoff from  21.4716 because the cutoff seemed overly generous
Group  18, IL_04346.10 has acceptance rules AlignmentScore >= -27.9350, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  27.9350
TP   100.00%, TN    97.50%, min    97.50%,  15 3D sequences,     0 alignment sequences, 1001 random sequences,   25 random matches, 15 NTs, cWW-cWW-tSH-tHH-cSH-tWH-tHS-cWW
Sensitivity 100.00%, Specificity  97.50%, Minimum  97.50% using method 8
Number of false positives with core edit > 0 is 25
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11
Motif index 12
Motif index 13
Motif index 14
Motif index 15


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_04600.1'
                     Signature: {'cWW-cWW-L-R-L-R-L-R-cWW-cWW'  ''}
                         NumNT: 14
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 12
                        NumBPh: 2
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 8
                      NumFixed: 28
                      OwnScore: -8.6710
                   OwnSequence: {'UCGAAAA*UCGAAAA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 14
            MeanSequenceLength: 14
               DeficitEditData: [1342×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 1342 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  20.7699 because the cutoff seemed overly generous
Group  19, IL_04600.1  has acceptance rules AlignmentScore >= -28.6710, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  28.6710
TP   100.00%, TN    97.09%, min    97.09%,   1 3D sequences,     0 alignment sequences, 1342 random sequences,   39 random matches, 14 NTs, cWW-cWW-L-R-L-R-L-R-cWW-cWW
Sensitivity 100.00%, Specificity  97.09%, Minimum  97.09% using method 8
Number of false positives with core edit > 0 is 39
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_04638.3'
                     Signature: {'cWW-tSH-tHW-tHS-cSH-cWW-L'  ''}
                         NumNT: 13
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 13
                        NumBPh: 1
                         NumBR: 3
                  NumInstances: 5
                      Truncate: 9
                      NumFixed: 28
                      OwnScore: [-8.8971 -8.8971 -8.8971 -9.6108 -9.9504]
                   OwnSequence: {'CAAGAUGAG*UUGAG'  'CAAGAUGAG*UUGAG'  'CAAGAUGAG*UUGAG'  'CGAGAUGAG*CUGAG'  'GGAAAAGAG*CUGAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [14 14 14 14 14]
            MeanSequenceLength: 14
               DeficitEditData: [2633×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

5 sequences from 3D structures
Using 2633 random sequences, 0 from an alignment, and 5 from 3D structures
Decreased cutoff from  20.2229 because the cutoff seemed overly generous
Group  20, IL_04638.3  has acceptance rules AlignmentScore >= -28.8971, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  28.8971
TP   100.00%, TN    96.32%, min    96.32%,   5 3D sequences,     0 alignment sequences, 2633 random sequences,   97 random matches, 13 NTs, cWW-tSH-tHW-tHS-cSH-cWW-L
Sensitivity 100.00%, Specificity  96.32%, Minimum  96.32% using method 8
Number of false positives with core edit > 0 is 97
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_04650.2'
                     Signature: {'cWW-cWW-L-cWW-L-R-L-L-cSH'  ''}
                         NumNT: 11
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 2
                         NumBR: 2
                  NumInstances: 4
                      Truncate: 10
                      NumFixed: 42
                      OwnScore: [-5.4994 -5.4994 -5.4994 -5.4994]
                   OwnSequence: {'AACAACCCCG*CU'  'AACAACCCCG*CU'  'AACAUCCCCG*CU'  'AACAUCCCCG*CU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [12 12 12 12]
            MeanSequenceLength: 12
               DeficitEditData: [1703×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 1703 random sequences, 0 from an alignment, and 4 from 3D structures
Decreased cutoff from  22.0808 because the cutoff seemed overly generous
Group  21, IL_04650.2  has acceptance rules AlignmentScore >= -25.4994, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.4994
TP   100.00%, TN    97.59%, min    97.59%,   4 3D sequences,     0 alignment sequences, 1703 random sequences,   41 random matches, 11 NTs, cWW-cWW-L-cWW-L-R-L-L-cSH
Sensitivity 100.00%, Specificity  97.59%, Minimum  97.59% using method 8
Number of false positives with core edit > 0 is 41
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1
Motif index 2
Motif index 3
Motif index 4


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_04736.1'
                     Signature: {'cWW-L-R-L-R-L-R-L-R-cWW'  ''}
                         NumNT: 12
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 7
                      NumFixed: 32
                      OwnScore: -8.3327
                   OwnSequence: {'CGCAUAG*CGCAUAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 14
            MeanSequenceLength: 14
               DeficitEditData: [2204×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 2204 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  21.1899 because the cutoff seemed overly generous
Group  22, IL_04736.1  has acceptance rules AlignmentScore >= -28.3327, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  28.3327
TP   100.00%, TN    97.41%, min    97.41%,   1 3D sequences,     0 alignment sequences, 2204 random sequences,   57 random matches, 12 NTs, cWW-L-R-L-R-L-R-L-R-cWW
Sensitivity 100.00%, Specificity  97.41%, Minimum  97.41% using method 8
Number of false positives with core edit > 0 is 57
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_04785.1'
                     Signature: {'cWW-L-R-L-R-cWW'  ''}
                         NumNT: 8
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 5
                      NumFixed: 16
                      OwnScore: [-6.7283 -8.1833]
                   OwnSequence: {'GGAG*CAGGC'  'CCCG*CCCG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 8]
            MeanSequenceLength: 8.5000
               DeficitEditData: [9584×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 9584 random sequences, 0 from an alignment, and 2 from 3D structures
Group  23, IL_04785.1  has acceptance rules AlignmentScore >= -26.7283, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.4762
TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 9578 random sequences,  383 random matches,  8 NTs, cWW-L-R-L-R-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 383
1 * Deficit + 3 * Core Edit <= 10.7478
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_05192.4'
                     Signature: {'cWW-L-R-L-R-L-cWW-L'  ''}
                         NumNT: 10
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 3
                      Truncate: 7
                      NumFixed: 36
                      OwnScore: [-9.7242 -9.0595 -9.0486]
                   OwnSequence: {'UAUUGG*CAGG'  'GGGUCG*CCCC'  'CGAACG*CAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10 10]
            MeanSequenceLength: 10
               DeficitEditData: [18620×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 18620 random sequences, 0 from an alignment, and 3 from 3D structures
Group  24, IL_05192.4  has acceptance rules AlignmentScore >= -29.0486, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  22.8091
TP   100.00%, TN    95.99%, min    95.99%,   3 3D sequences,     0 alignment sequences, 18619 random sequences,  746 random matches, 10 NTs, cWW-L-R-L-R-L-cWW-L
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 746
1 * Deficit + 3 * Core Edit <= 13.7605
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_05472.1'
                     Signature: {'cWW-L-R-L-R-L-R-L-R-L-cWW-L'  ''}
                         NumNT: 14
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 11
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 9
                      NumFixed: 56
                      OwnScore: -9.6565
                   OwnSequence: {'GUUUUUAACG*CUUUUC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 16
            MeanSequenceLength: 16
               DeficitEditData: [62×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 62 random sequences, 0 from an alignment, and 1 from 3D structures
Group  25, IL_05472.1  has acceptance rules AlignmentScore >= -29.6565, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  29.0502
TP   100.00%, TN    96.77%, min    96.77%,   1 3D sequences,     0 alignment sequences,   62 random sequences,    2 random matches, 14 NTs, cWW-L-R-L-R-L-R-L-R-L-cWW-L
Sensitivity 100.00%, Specificity  96.77%, Minimum  96.77% using method 6
Number of false positives with core edit > 0 is 2
1 * Deficit + 3 * Core Edit <= 19.3937
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_06029.1'
                     Signature: {'cWW-L-R-L-R-L-cWW-L-L-R-L-R-L-R-L'  ''}
                         NumNT: 17
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 14
                      NumFixed: 58
                      OwnScore: -15.4384
                   OwnSequence: {'CCGACCUUGAAAUACC*GGGAGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 22
            MeanSequenceLength: 22
               DeficitEditData: [17.3941 5]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 1 random sequences, 0 from an alignment, and 1 from 3D structures
Group  26, IL_06029.1  has acceptance rules AlignmentScore >= -35.4384, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  40.4384
TP   100.00%, TN   100.00%, min   100.00%,   1 3D sequences,     0 alignment sequences,    1 random sequences,    0 random matches, 17 NTs, cWW-L-R-L-R-L-cWW-L-L-R-L-R-L-R-L
Sensitivity 100.00%, Specificity 100.00%, Minimum 100.00% using method 1
Number of false positives with core edit > 0 is 0
1 * Deficit + 3 * Core Edit <= 25.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_06136.2'
                     Signature: {'cWW-tHS-cWW-tHS-tSH-tSH-cWW'  ''}
                         NumNT: 12
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 13
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 6
                      Truncate: 7
                      NumFixed: 20
                      OwnScore: [-9.5549 -9.5549 -9.5549 -9.8466 -9.8466 -12.7859]
                   OwnSequence: {'GGGAAC*GGGAAC'  'GGGAAC*GGGAAC'  'GGGAAC*GGGAAC'  'CGGAUG*CGGAUG'  'CGGAUG*CGGAUG'  'GCGGAG*UGAAAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [12 12 12 12 12 12]
            MeanSequenceLength: 12
               DeficitEditData: [4111×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

6 sequences from 3D structures
Using 4111 random sequences, 0 from an alignment, and 6 from 3D structures
Group  27, IL_06136.2  has acceptance rules AlignmentScore >= -29.5549, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.0608
TP   100.00%, TN    96.01%, min    96.01%,   6 3D sequences,     0 alignment sequences, 4111 random sequences,  164 random matches, 12 NTs, cWW-tHS-cWW-tHS-tSH-tSH-cWW
Sensitivity 100.00%, Specificity  96.01%, Minimum  96.01% using method 6
Number of false positives with core edit > 0 is 164
1 * Deficit + 3 * Core Edit <= 14.5059
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_06300.1'
                     Signature: {'cWW-L-R-L-R-L-cWW'  ''}
                         NumNT: 9
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 6
                      NumFixed: 26
                      OwnScore: -5.5781
                   OwnSequence: {'UGAUG*UUAA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 9
            MeanSequenceLength: 9
               DeficitEditData: [10787×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 10787 random sequences, 0 from an alignment, and 1 from 3D structures
Group  28, IL_06300.1  has acceptance rules AlignmentScore >= -25.5781, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  19.4440
TP   100.00%, TN    95.98%, min    95.98%,   1 3D sequences,     0 alignment sequences, 10786 random sequences,  434 random matches,  9 NTs, cWW-L-R-L-R-L-cWW
Sensitivity 100.00%, Specificity  95.98%, Minimum  95.98% using method 6
Number of false positives with core edit > 0 is 434
1 * Deficit + 3 * Core Edit <= 13.8658
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_06549.2'
                     Signature: {'cWW-cWW'  ''}
                         NumNT: 4
                  NumBasepairs: 2
                    Structured: 0
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 6
                      Truncate: 3
                      NumFixed: 12
                      OwnScore: [-6.1034 -6.1034 -6.5216 -6.0151 -6.5216 -7.3144]
                   OwnSequence: {'GGG*UAAUC'  'GGG*UAAUC'  'GGA*UAACC'  'GGG*CAAUC'  'GGA*UAACC'  'GCG*CAAUC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8 8 8 8 8]
            MeanSequenceLength: 8
               DeficitEditData: [12451×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

6 sequences from 3D structures
Using 12451 random sequences, 0 from an alignment, and 6 from 3D structures
Group  29, IL_06549.2  has acceptance rules AlignmentScore >= -26.0151, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.3135
TP   100.00%, TN    96.00%, min    96.00%,   6 3D sequences,     0 alignment sequences, 12437 random sequences,  497 random matches,  4 NTs, cWW-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 497
1 * Deficit + 3 * Core Edit <= 10.2984
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_06691.1'
                     Signature: {'cWW-cWS-L-R-L-R-cWW-L'  ''}
                         NumNT: 10
                  NumBasepairs: 10
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 7
                      NumFixed: 34
                      OwnScore: [-7.0830 -6.0145]
                   OwnSequence: {'GAACUC*GUUGC'  'GCGACCG*CAAAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 12]
            MeanSequenceLength: 11.5000
               DeficitEditData: [3606×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 3606 random sequences, 0 from an alignment, and 2 from 3D structures
Decreased cutoff from  20.9748 because the cutoff seemed overly generous
Group  30, IL_06691.1  has acceptance rules AlignmentScore >= -26.0145, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.0145
TP   100.00%, TN    97.09%, min    97.09%,   2 3D sequences,     0 alignment sequences, 3605 random sequences,  105 random matches, 10 NTs, cWW-cWS-L-R-L-R-cWW-L
Sensitivity 100.00%, Specificity  97.09%, Minimum  97.09% using method 8
Number of false positives with core edit > 0 is 105
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_07039.3'
                     Signature: {'cWW-L-cWW'  ''}
                         NumNT: 5
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 16
                      Truncate: 4
                      NumFixed: 16
                      OwnScore: [-3.1610 -3.1610 -3.1610 -3.1610 -3.1610 -3.1610 -5.6571 -5.1463 -5.1463 -3.1610 -3.4097 -3.6917 -3.6917 … ]
                   OwnSequence: {1×16 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5]
            MeanSequenceLength: 5
               DeficitEditData: [4993×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

16 sequences from 3D structures
Using 4993 random sequences, 0 from an alignment, and 16 from 3D structures
Group  31, IL_07039.3  has acceptance rules AlignmentScore >= -23.1610, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.2552
TP   100.00%, TN    95.99%, min    95.99%,  16 3D sequences,     0 alignment sequences, 3993 random sequences,  160 random matches,  5 NTs, cWW-L-cWW
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 160
1 * Deficit + 3 * Core Edit <= 12.0942
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11
Motif index 12
Motif index 13
Motif index 14
Motif index 15
Motif index 16


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_07171.1'
                     Signature: {'cWW-L-cWW-L'  ''}
                         NumNT: 6
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 5
                      NumFixed: 20
                      OwnScore: -4.8363
                   OwnSequence: {'ACGUG*UU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 7
            MeanSequenceLength: 7
               DeficitEditData: [12000×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 12000 random sequences, 0 from an alignment, and 1 from 3D structures
Group  32, IL_07171.1  has acceptance rules AlignmentScore >= -24.8363, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.3339
TP   100.00%, TN    95.71%, min    95.71%,   1 3D sequences,     0 alignment sequences, 11991 random sequences,  514 random matches,  6 NTs, cWW-L-cWW-L
Sensitivity 100.00%, Specificity  95.71%, Minimum  95.71% using method 6
Number of false positives with core edit > 0 is 514
1 * Deficit + 3 * Core Edit <= 10.4977
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_07173.1'
                     Signature: {'cWW-L-R-L-cWW-L'  ''}
                         NumNT: 8
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 6
                      NumFixed: 28
                      OwnScore: -6.2247
                   OwnSequence: {'AUAGUC*GCU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 9
            MeanSequenceLength: 9
               DeficitEditData: [17215×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 17215 random sequences, 0 from an alignment, and 1 from 3D structures
Group  33, IL_07173.1  has acceptance rules AlignmentScore >= -26.2247, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  21.0983
TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences, 17213 random sequences,  690 random matches,  8 NTs, cWW-L-R-L-cWW-L
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 690
1 * Deficit + 3 * Core Edit <= 14.8736
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_07469.2'
                     Signature: {'cWW-tSH-cWW-cSH-R-cWW'  ''}
                         NumNT: 10
                  NumBasepairs: 7
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 3
                      Truncate: 7
                      NumFixed: 26
                      OwnScore: [-3.5301 -3.5301 -10.4540]
                   OwnSequence: {'UAAGCG*CAUA'  'UAAGCG*CAUA'  'AGUGCG*CGUU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10 10]
            MeanSequenceLength: 10
               DeficitEditData: [2250×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 2250 random sequences, 0 from an alignment, and 3 from 3D structures
Group  34, IL_07469.2  has acceptance rules AlignmentScore >= -23.5301, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  22.2182
TP   100.00%, TN    96.00%, min    96.00%,   3 3D sequences,     0 alignment sequences, 2250 random sequences,   90 random matches, 10 NTs, cWW-tSH-cWW-cSH-R-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 90
1 * Deficit + 3 * Core Edit <= 18.6881
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_07785.1'
                     Signature: {'cWW-cWW-cWW'  ''}
                         NumNT: 6
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 33
                      Truncate: 4
                      NumFixed: 14
                      OwnScore: [-5.4427 -5.3565 -5.4284 -5.9003 -7.1708 -5.2110 -6.7155 -7.3713 -5.9003 -6.7155 -5.9003 -5.9003 -5.4284 … ]
                   OwnSequence: {1×33 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 6 6 6 6 6 6 6 6 6 6 6 6 7 7 8 8 8 8 7 7 7 8 8 8 7 7 8 7 7 7 8]
            MeanSequenceLength: 6.8485
               DeficitEditData: [11460×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

33 sequences from 3D structures
Using 11460 random sequences, 0 from an alignment, and 33 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group  35, IL_07785.1  has acceptance rules AlignmentScore >= -25.1354, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  14.6354
TP   100.00%, TN    87.46%, min    87.46%,  33 3D sequences,     0 alignment sequences, 11195 random sequences, 1404 random matches,  6 NTs, cWW-cWW-cWW
Sensitivity 100.00%, Specificity  87.46%, Minimum  87.46% using method 11
Number of false positives with core edit > 0 is 1404
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11
Motif index 12
Motif index 13
Motif index 14
Motif index 15
Motif index 16
Motif index 17
Motif index 18
Motif index 19
Motif index 20
Motif index 21
Motif index 22
Motif index 23
Motif index 24
Motif index 25
Motif index 26
Motif index 27
Motif index 28
Motif index 29
Motif index 30
Motif index 31
Motif index 32
Motif index 33


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_08770.1'
                     Signature: {'cWW-L-R-cWW'  ''}
                         NumNT: 6
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 5
                      Truncate: 4
                      NumFixed: 20
                      OwnScore: [-6.3207 -6.3207 -8.3477 -6.0197 -6.4540]
                   OwnSequence: {'GAAG*CAC'  'GAAG*CAC'  'ACAG*CGU'  'CUG*CAG'  'ACA*UUU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 7 7 6 6]
            MeanSequenceLength: 6.6000
               DeficitEditData: [13029×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

5 sequences from 3D structures
Using 13029 random sequences, 0 from an alignment, and 5 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group  36, IL_08770.1  has acceptance rules AlignmentScore >= -26.0197, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.5197
TP   100.00%, TN    82.49%, min    82.49%,   5 3D sequences,     0 alignment sequences, 12784 random sequences, 2238 random matches,  6 NTs, cWW-L-R-cWW
Sensitivity 100.00%, Specificity  82.49%, Minimum  82.49% using method 11
Number of false positives with core edit > 0 is 2238
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_09044.1'
                     Signature: {'cWW-tSH-tHH-L-tHS-cWW'  ''}
                         NumNT: 11
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 3
                         NumBR: 2
                  NumInstances: 1
                      Truncate: 7
                      NumFixed: 22
                      OwnScore: -6.4802
                   OwnSequence: {'UGACAAC*GGAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 12
            MeanSequenceLength: 12
               DeficitEditData: [5543×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 5543 random sequences, 0 from an alignment, and 1 from 3D structures
Group  37, IL_09044.1  has acceptance rules AlignmentScore >= -26.4802, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.7349
TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences, 5543 random sequences,  222 random matches, 11 NTs, cWW-tSH-tHH-L-tHS-cWW
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 222
1 * Deficit + 3 * Core Edit <= 18.2547
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_09129.2'
                     Signature: {'cWW-L-R-tWH-L-R-L-tWW-cWW'  ''}
                         NumNT: 14
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 11
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 8
                      NumFixed: 34
                      OwnScore: [-7.8645 -7.8645]
                   OwnSequence: {'UACAAAG*CAAAAAG'  'UACAAAG*CAUAAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [14 14]
            MeanSequenceLength: 14
               DeficitEditData: [1860×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 1860 random sequences, 0 from an alignment, and 2 from 3D structures
Group  38, IL_09129.2  has acceptance rules AlignmentScore >= -27.8645, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  27.7553
TP   100.00%, TN    96.02%, min    96.02%,   2 3D sequences,     0 alignment sequences, 1860 random sequences,   74 random matches, 14 NTs, cWW-L-R-tWH-L-R-L-tWW-cWW
Sensitivity 100.00%, Specificity  96.02%, Minimum  96.02% using method 6
Number of false positives with core edit > 0 is 74
1 * Deficit + 3 * Core Edit <= 19.8909
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_09570.1'
                     Signature: {'cWW-L-R-L-R-L-cWW-L-L-R'  ''}
                         NumNT: 12
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 9
                      NumFixed: 44
                      OwnScore: -8.7071
                   OwnSequence: {'GGCCGUGC*GAGC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 12
            MeanSequenceLength: 12
               DeficitEditData: [5722×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 5722 random sequences, 0 from an alignment, and 1 from 3D structures
Group  39, IL_09570.1  has acceptance rules AlignmentScore >= -28.7071, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  28.6031
TP   100.00%, TN    95.93%, min    95.93%,   1 3D sequences,     0 alignment sequences, 5722 random sequences,  233 random matches, 12 NTs, cWW-L-R-L-R-L-cWW-L-L-R
Sensitivity 100.00%, Specificity  95.93%, Minimum  95.93% using method 6
Number of false positives with core edit > 0 is 233
1 * Deficit + 3 * Core Edit <= 19.8960
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_09705.15'
                     Signature: {'cWW-tSH-tHS-cWW'  ''}
                         NumNT: 8
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 0
                         NumBR: 2
                  NumInstances: 34
                      Truncate: 5
                      NumFixed: 16
                      OwnScore: [-5.0731 -5.0731 -5.0731 -5.0731 -6.0199 -5.5725 -6.6050 -6.0199 -6.4249 -6.6050 -5.0731 -5.0731 -5.7155 … ]
                   OwnSequence: {1×34 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 10 10 8 8 8 8 8]
            MeanSequenceLength: 8.1176
               DeficitEditData: [7852×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

34 sequences from 3D structures
Using 7852 random sequences, 0 from an alignment, and 34 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group  40, IL_09705.15 has acceptance rules AlignmentScore >= -25.0731, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  14.5731
TP   100.00%, TN    95.71%, min    95.71%,  34 3D sequences,     0 alignment sequences, 7745 random sequences,  332 random matches,  8 NTs, cWW-tSH-tHS-cWW
Sensitivity 100.00%, Specificity  95.71%, Minimum  95.71% using method 11
Number of false positives with core edit > 0 is 332
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11
Motif index 12
Motif index 13
Motif index 14
Motif index 15
Motif index 16
Motif index 17
Motif index 18
Motif index 19
Motif index 20
Motif index 21
Motif index 22
Motif index 23
Motif index 24
Motif index 25
Motif index 26
Motif index 27
Motif index 28
Motif index 29
Motif index 30
Motif index 31
Motif index 32
Motif index 33
Motif index 34


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_09908.1'
                     Signature: {'cWW-L-tHH-L-R-L-cWW-L'  ''}
                         NumNT: 11
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 11
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 8
                      NumFixed: 28
                      OwnScore: -8.0125
                   OwnSequence: {'CACAAAC*GGAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 11
            MeanSequenceLength: 11
               DeficitEditData: [9977×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 9977 random sequences, 0 from an alignment, and 1 from 3D structures
Group  41, IL_09908.1  has acceptance rules AlignmentScore >= -28.0125, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.4068
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 9976 random sequences,  399 random matches, 11 NTs, cWW-L-tHH-L-R-L-cWW-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 399
1 * Deficit + 3 * Core Edit <= 16.3943
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_09990.4'
                     Signature: {'cWW-L-R-L-cWW'  ''}
                         NumNT: 7
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 5
                      NumFixed: 18
                      OwnScore: [-4.4480 -6.2988]
                   OwnSequence: {'GACU*ACC'  'GCCC*GGC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 7]
            MeanSequenceLength: 7
               DeficitEditData: [8164×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 8164 random sequences, 0 from an alignment, and 2 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group  42, IL_09990.4  has acceptance rules AlignmentScore >= -24.4480, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.9480
TP   100.00%, TN    95.57%, min    95.57%,   2 3D sequences,     0 alignment sequences, 8140 random sequences,  361 random matches,  7 NTs, cWW-L-R-L-cWW
Sensitivity 100.00%, Specificity  95.57%, Minimum  95.57% using method 11
Number of false positives with core edit > 0 is 361
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_10167.6'
                     Signature: {'cWW-cHW-cWW'  ''}
                         NumNT: 6
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 51
                      Truncate: 4
                      NumFixed: 14
                      OwnScore: [-2.9779 -2.9779 -2.9779 -2.9779 -3.9194 -2.9779 -2.9779 -2.9779 -3.8959 -2.9779 -2.9779 -3.6220 -3.9194 … ]
                   OwnSequence: {1×51 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 7 6 7 6 6]
            MeanSequenceLength: 6.0392
               DeficitEditData: [5505×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

51 sequences from 3D structures
Using 5505 random sequences, 0 from an alignment, and 51 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group  43, IL_10167.6  has acceptance rules AlignmentScore >= -22.9779, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  12.4779
TP    98.04%, TN    89.55%, min    89.55%,  51 3D sequences,     0 alignment sequences, 4974 random sequences,  520 random matches,  6 NTs, cWW-cHW-cWW
Sensitivity  98.04%, Specificity  89.55%, Minimum  89.55% using method 11
Number of false positives with core edit > 0 is 520
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11
Motif index 12
Motif index 13
Motif index 14
Motif index 15
Motif index 16
Motif index 17
Motif index 18
Motif index 19
Motif index 20
Motif index 21
Motif index 22
Motif index 23
Motif index 24
Motif index 25
Motif index 26
Motif index 27
Motif index 28
Motif index 29
Motif index 30
Motif index 31
Motif index 32
Motif index 33
Motif index 34
Motif index 35
Motif index 36
Motif index 37
Motif index 38
Motif index 39
Motif index 40
Motif index 41
Motif index 42
Motif index 43
Motif index 44
Motif index 45
Motif index 46
Motif index 47
Motif index 48
Motif index 49
Motif index 50
Motif index 51


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_10389.1'
                     Signature: {'cWW-L-cWW-L-cWW'  ''}
                         NumNT: 8
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 6
                      NumFixed: 22
                      OwnScore: [-6.9051 -8.0816]
                   OwnSequence: {'GCAGC*GAC'  'CCCUUG*CAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 9]
            MeanSequenceLength: 8.5000
               DeficitEditData: [15899×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 15899 random sequences, 0 from an alignment, and 2 from 3D structures
Group  44, IL_10389.1  has acceptance rules AlignmentScore >= -26.9051, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  18.5460
TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 15894 random sequences,  636 random matches,  8 NTs, cWW-L-cWW-L-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 636
1 * Deficit + 3 * Core Edit <= 11.6409
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_10484.1'
                     Signature: {'cWW-tSH-tHS-cWW'  ''}
                         NumNT: 8
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 0
                         NumBR: 2
                  NumInstances: 2
                      Truncate: 5
                      NumFixed: 16
                      OwnScore: [-5.9368 -6.4236]
                   OwnSequence: {'UUCG*UUCG'  'UGAG*UAAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 9]
            MeanSequenceLength: 8.5000
               DeficitEditData: [7861×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 7861 random sequences, 0 from an alignment, and 2 from 3D structures
Group  45, IL_10484.1  has acceptance rules AlignmentScore >= -25.9368, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.4795
TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 7853 random sequences,  314 random matches,  8 NTs, cWW-tSH-tHS-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 314
1 * Deficit + 3 * Core Edit <= 11.5427
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_10569.1'
                     Signature: {'cWW-L-cWW'  ''}
                         NumNT: 5
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 4
                      NumFixed: 18
                      OwnScore: [-3.8359 -3.5532]
                   OwnSequence: {'AAA*UU'  'CAG*CG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [5 5]
            MeanSequenceLength: 5
               DeficitEditData: [6316×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 6316 random sequences, 0 from an alignment, and 2 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group  46, IL_10569.1  has acceptance rules AlignmentScore >= -23.5532, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.0532
TP   100.00%, TN    82.30%, min    82.30%,   2 3D sequences,     0 alignment sequences, 6067 random sequences, 1074 random matches,  5 NTs, cWW-L-cWW
Sensitivity 100.00%, Specificity  82.30%, Minimum  82.30% using method 11
Number of false positives with core edit > 0 is 1074
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_10796.1'
                     Signature: {'cWW-L-R-cWW'  ''}
                         NumNT: 6
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 2
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 4
                      NumFixed: 20
                      OwnScore: -3.5911
                   OwnSequence: {'UCG*UCG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 6
            MeanSequenceLength: 6
               DeficitEditData: [6163×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 6163 random sequences, 0 from an alignment, and 1 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group  47, IL_10796.1  has acceptance rules AlignmentScore >= -23.5911, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.0911
TP   100.00%, TN    95.64%, min    95.64%,   1 3D sequences,     0 alignment sequences, 6130 random sequences,  267 random matches,  6 NTs, cWW-L-R-cWW
Sensitivity 100.00%, Specificity  95.64%, Minimum  95.64% using method 11
Number of false positives with core edit > 0 is 267
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_11344.2'
                     Signature: {'cWW-cSS-L-cWW'  ''}
                         NumNT: 5
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 1
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 4
                      NumFixed: 16
                      OwnScore: [-9.2558 -8.4085]
                   OwnSequence: {'CUAAUC*GAUG'  'CGGACC*GAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10]
            MeanSequenceLength: 10
               DeficitEditData: [18727×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 18727 random sequences, 0 from an alignment, and 2 from 3D structures
Group  48, IL_11344.2  has acceptance rules AlignmentScore >= -28.4085, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  21.3298
TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 18726 random sequences,  749 random matches,  5 NTs, cWW-cSS-L-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 749
1 * Deficit + 3 * Core Edit <= 12.9213
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_11399.2'
                     Signature: {'cWW-cHW-L-R-L-cWW'  ''}
                         NumNT: 9
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 3
                      Truncate: 6
                      NumFixed: 26
                      OwnScore: [-4.7105 -4.7105 -7.8520]
                   OwnSequence: {'AGGAC*GGGU'  'AGGAC*GGGU'  'AAAAG*CGCU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 9]
            MeanSequenceLength: 9
               DeficitEditData: [10350×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 10350 random sequences, 0 from an alignment, and 3 from 3D structures
Group  49, IL_11399.2  has acceptance rules AlignmentScore >= -24.7105, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.7864
TP   100.00%, TN    95.99%, min    95.99%,   3 3D sequences,     0 alignment sequences, 10345 random sequences,  415 random matches,  9 NTs, cWW-cHW-L-R-L-cWW
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 415
1 * Deficit + 3 * Core Edit <= 13.0760
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_11415.1'
                     Signature: {'cWW-L-R-L-cWW-L'  ''}
                         NumNT: 8
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 6
                      NumFixed: 22
                      OwnScore: -4.5092
                   OwnSequence: {'UUCCG*UGA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 8
            MeanSequenceLength: 8
               DeficitEditData: [10575×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 10575 random sequences, 0 from an alignment, and 1 from 3D structures
Group  50, IL_11415.1  has acceptance rules AlignmentScore >= -24.5092, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  19.7840
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 10572 random sequences,  423 random matches,  8 NTs, cWW-L-R-L-cWW-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 423
1 * Deficit + 3 * Core Edit <= 15.2748
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_12566.4'
                     Signature: {'cWW-L-tHS-L-cWW-L'  ''}
                         NumNT: 9
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 2
                         NumBR: 2
                  NumInstances: 5
                      Truncate: 7
                      NumFixed: 26
                      OwnScore: [-3.8264 -3.8264 -3.8264 -4.9250 -7.2405]
                   OwnSequence: {'GAGAAC*GAC'  'GAGAAC*GAC'  'GAGAAC*GAC'  'GCGAAC*GAC'  'GAGCAAC*GGC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 9 9 10]
            MeanSequenceLength: 9.2000
               DeficitEditData: [9831×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

5 sequences from 3D structures
Using 9831 random sequences, 0 from an alignment, and 5 from 3D structures
Group  51, IL_12566.4  has acceptance rules AlignmentScore >= -23.8264, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  18.3422
TP   100.00%, TN    96.00%, min    96.00%,   5 3D sequences,     0 alignment sequences, 9828 random sequences,  393 random matches,  9 NTs, cWW-L-tHS-L-cWW-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 393
1 * Deficit + 3 * Core Edit <= 14.5158
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_12697.1'
                     Signature: {'cWW-cWW-L-R-tHS-cWW'  ''}
                         NumNT: 10
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 2
                      Truncate: 6
                      NumFixed: 18
                      OwnScore: [-7.9241 -7.9241]
                   OwnSequence: {'UCAAA*UGACAA'  'UCAAA*UGACAA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11]
            MeanSequenceLength: 11
               DeficitEditData: [6939×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 6939 random sequences, 0 from an alignment, and 2 from 3D structures
Group  52, IL_12697.1  has acceptance rules AlignmentScore >= -27.9241, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  23.7110
TP   100.00%, TN    95.99%, min    95.99%,   2 3D sequences,     0 alignment sequences, 6939 random sequences,  278 random matches, 10 NTs, cWW-cWW-L-R-tHS-cWW
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 278
1 * Deficit + 3 * Core Edit <= 15.7870
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_12745.1'
                     Signature: {'cWW-tWH-tWH-tHW-tHW-cWW'  ''}
                         NumNT: 12
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 12
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 7
                      NumFixed: 20
                      OwnScore: -6.7221
                   OwnSequence: {'GACAAC*GCUAAUC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 13
            MeanSequenceLength: 13
               DeficitEditData: [2037×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 2037 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  21.6062 because the cutoff seemed overly generous
Group  53, IL_12745.1  has acceptance rules AlignmentScore >= -26.7221, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  27.1372
TP   100.00%, TN    97.99%, min    97.99%,   1 3D sequences,     0 alignment sequences, 2036 random sequences,   41 random matches, 12 NTs, cWW-tWH-tWH-tHW-tHW-cWW
Sensitivity 100.00%, Specificity  97.99%, Minimum  97.99% using method 8
Number of false positives with core edit > 0 is 41
1 * Deficit + 3 * Core Edit <= 20.4151
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_13358.1'
                     Signature: {'cWW-L-R-L-R-L-R-L-cWW-L-L'  ''}
                         NumNT: 13
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 9
                      NumFixed: 42
                      OwnScore: -8.9956
                   OwnSequence: {'UUCUUUGUA*UGGGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 14
            MeanSequenceLength: 14
               DeficitEditData: [548×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 548 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  22.7442 because the cutoff seemed overly generous
Group  54, IL_13358.1  has acceptance rules AlignmentScore >= -28.9956, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  30.3790
TP   100.00%, TN    97.99%, min    97.99%,   1 3D sequences,     0 alignment sequences,  548 random sequences,   11 random matches, 13 NTs, cWW-L-R-L-R-L-R-L-cWW-L-L
Sensitivity 100.00%, Specificity  97.99%, Minimum  97.99% using method 8
Number of false positives with core edit > 0 is 11
1 * Deficit + 3 * Core Edit <= 21.3834
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_13394.1'
                     Signature: {'cWW-L-R-L-R-L-R-L-R-L-R-L-R-L-R-L-R-L-R-L-R'  ''}
                         NumNT: 21
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 15
                        NumBPh: 2
                         NumBR: 2
                  NumInstances: 1
                      Truncate: 16
                      NumFixed: 72
                      OwnScore: -16.4920
                   OwnSequence: {'AAUGUGCCUUCGGGAAC*GAAGUU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 23
            MeanSequenceLength: 23
               DeficitEditData: [0×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 0 random sequences, 0 from an alignment, and 1 from 3D structures
No random sequence matches, so essentially no model-specific cutoff imposed
Decreased cutoff to  25.0000 so that it is possible to reject matches
Group  55, IL_13394.1  has acceptance rules AlignmentScore >= -36.4920, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  41.4920
TP   100.00%, TN      NaN%, min   100.00%,   1 3D sequences,     0 alignment sequences,    0 random sequences,    0 random matches, 21 NTs, cWW-L-R-L-R-L-R-L-R-L-R-L-R-L-R-L-R-L-R-L-R
Sensitivity 100.00%, Specificity    NaN%, Minimum 100.00% using method 12
Number of false positives with core edit > 0 is 0
1 * Deficit + 3 * Core Edit <= 25.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_13404.2'
                     Signature: {'cWW-cWW-cWW-cWW'  ''}
                         NumNT: 8
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 10
                      Truncate: 5
                      NumFixed: 16
                      OwnScore: [-4.2188 -4.2188 -4.2188 -4.2188 -4.2188 -4.2188 -4.2188 -4.2188 -13.8375 -9.5677]
                   OwnSequence: {1×10 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8 8 8 8 8 8 8 9 8]
            MeanSequenceLength: 8.1000
               DeficitEditData: [5568×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

10 sequences from 3D structures
Using 5568 random sequences, 0 from an alignment, and 10 from 3D structures
Group  56, IL_13404.2  has acceptance rules AlignmentScore >= -24.2188, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.9499
TP   100.00%, TN    96.00%, min    96.00%,  10 3D sequences,     0 alignment sequences, 5555 random sequences,  222 random matches,  8 NTs, cWW-cWW-cWW-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 222
1 * Deficit + 3 * Core Edit <= 12.7311
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_13874.1'
                     Signature: {'cWW-cWH-tHS-cWW-cSH-cWH-cHW-cWW'  ''}
                         NumNT: 12
                  NumBasepairs: 8
                    Structured: 1
                     NumStacks: 12
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 8
                      NumFixed: 30
                      OwnScore: -5.8499
                   OwnSequence: {'UGGAGGGG*CGGUCG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 14
            MeanSequenceLength: 14
               DeficitEditData: [523×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 523 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  23.7403 because the cutoff seemed overly generous
Group  57, IL_13874.1  has acceptance rules AlignmentScore >= -25.8499, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  28.2659
TP   100.00%, TN    98.09%, min    98.09%,   1 3D sequences,     0 alignment sequences,  523 random sequences,   10 random matches, 12 NTs, cWW-cWH-tHS-cWW-cSH-cWH-cHW-cWW
Sensitivity 100.00%, Specificity  98.09%, Minimum  98.09% using method 8
Number of false positives with core edit > 0 is 10
1 * Deficit + 3 * Core Edit <= 22.4160
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_14177.2'
                     Signature: {'cWW-L-R-L-cWW'  ''}
                         NumNT: 7
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 2
                      Truncate: 5
                      NumFixed: 24
                      OwnScore: [-5.3143 -5.6413]
                   OwnSequence: {'CCUAAG*UAG'  'CCUAAC*GGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9]
            MeanSequenceLength: 9
               DeficitEditData: [16964×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 16964 random sequences, 0 from an alignment, and 2 from 3D structures
Group  58, IL_14177.2  has acceptance rules AlignmentScore >= -25.3143, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  19.3131
TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 16959 random sequences,  678 random matches,  7 NTs, cWW-L-R-L-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 678
1 * Deficit + 3 * Core Edit <= 13.9988
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_14368.1'
                     Signature: {'cWW-L-cWW-cSH'  ''}
                         NumNT: 6
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 6
                      Truncate: 5
                      NumFixed: 26
                      OwnScore: [-2.4141 -2.4141 -2.4141 -2.4141 -2.4141 -10.1114]
                   OwnSequence: {'CUAA*UG'  'CUAA*UG'  'CUAA*UG'  'CUAA*UG'  'CUAA*UG'  'GAGCA*UU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 6 6 6 7]
            MeanSequenceLength: 6.1667
               DeficitEditData: [8365×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

6 sequences from 3D structures
Using 8365 random sequences, 0 from an alignment, and 6 from 3D structures
Group  59, IL_14368.1  has acceptance rules AlignmentScore >= -22.4141, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  12.8515
TP   100.00%, TN    95.98%, min    95.98%,   6 3D sequences,     0 alignment sequences, 8260 random sequences,  332 random matches,  6 NTs, cWW-L-cWW-cSH
Sensitivity 100.00%, Specificity  95.98%, Minimum  95.98% using method 6
Number of false positives with core edit > 0 is 332
1 * Deficit + 3 * Core Edit <= 10.4374
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_14688.1'
                     Signature: {'cWW-cWW-cWW'  ''}
                         NumNT: 6
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 5
                      Truncate: 4
                      NumFixed: 14
                      OwnScore: [-6.3837 -6.3837 -8.3858 -6.0487 -5.9729]
                   OwnSequence: {'GGU*AUAC'  'GGU*AUAC'  'UAC*GACG'  'ACC*GUU'  'UUU*ACA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 7 7 6 6]
            MeanSequenceLength: 6.6000
               DeficitEditData: [10616×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

5 sequences from 3D structures
Using 10616 random sequences, 0 from an alignment, and 5 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group  60, IL_14688.1  has acceptance rules AlignmentScore >= -25.9729, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.4729
TP   100.00%, TN    85.72%, min    85.72%,   5 3D sequences,     0 alignment sequences, 10496 random sequences, 1499 random matches,  6 NTs, cWW-cWW-cWW
Sensitivity 100.00%, Specificity  85.72%, Minimum  85.72% using method 11
Number of false positives with core edit > 0 is 1499
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_15052.4'
                     Signature: {'cWW-L-cWW-L'  ''}
                         NumNT: 6
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 8
                      Truncate: 5
                      NumFixed: 22
                      OwnScore: [-4.0784 -4.0784 -4.4067 -7.0039 -4.1307 -4.3207 -4.3405 -4.3405]
                   OwnSequence: {'AAAC*GU'  'AAAC*GU'  'CAGC*GG'  'CCAGC*GG'  'UAAC*GA'  'UAAU*AA'  'GUAG*CC'  'GUAG*CC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 6 7 6 6 6 6]
            MeanSequenceLength: 6.1250
               DeficitEditData: [7648×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

8 sequences from 3D structures
Using 7648 random sequences, 0 from an alignment, and 8 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group  61, IL_15052.4  has acceptance rules AlignmentScore >= -24.0784, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.5784
TP   100.00%, TN    90.02%, min    90.02%,   8 3D sequences,     0 alignment sequences, 7382 random sequences,  737 random matches,  6 NTs, cWW-L-cWW-L
Sensitivity 100.00%, Specificity  90.02%, Minimum  90.02% using method 11
Number of false positives with core edit > 0 is 737
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_15107.1'
                     Signature: {'cWW-R-L-R-L-R-L-R-L-R-L-R-L-L-L-cWW'  ''}
                         NumNT: 18
                  NumBasepairs: 8
                    Structured: 1
                     NumStacks: 16
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 11
                      NumFixed: 32
                      OwnScore: -13.5141
                   OwnSequence: {'CCCUUGGCAGC*GAUACCAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 19
            MeanSequenceLength: 19
               DeficitEditData: [5×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 5 random sequences, 0 from an alignment, and 1 from 3D structures
Group  62, IL_15107.1  has acceptance rules AlignmentScore >= -33.5141, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  38.5141
TP   100.00%, TN   100.00%, min   100.00%,   1 3D sequences,     0 alignment sequences,    5 random sequences,    0 random matches, 18 NTs, cWW-R-L-R-L-R-L-R-L-R-L-R-L-L-L-cWW
Sensitivity 100.00%, Specificity 100.00%, Minimum 100.00% using method 1
Number of false positives with core edit > 0 is 0
1 * Deficit + 3 * Core Edit <= 25.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_15218.1'
                     Signature: {'cWW-L-cWW-L-L-R-L-R-L-R-L'  ''}
                         NumNT: 13
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 12
                      NumFixed: 48
                      OwnScore: [-10.3814 -10.3814]
                   OwnSequence: {'CACAGCAGAAG*CG'  'CAUGGUCCCAG*CG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [13 13]
            MeanSequenceLength: 13
               DeficitEditData: [5040×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 5040 random sequences, 0 from an alignment, and 2 from 3D structures
Group  63, IL_15218.1  has acceptance rules AlignmentScore >= -30.3814, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  28.1255
TP   100.00%, TN    95.99%, min    95.99%,   2 3D sequences,     0 alignment sequences, 5040 random sequences,  202 random matches, 13 NTs, cWW-L-cWW-L-L-R-L-R-L-R-L
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 202
1 * Deficit + 3 * Core Edit <= 17.7441
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_15698.3'
                     Signature: {'cWW-L-R-L-cWW'  ''}
                         NumNT: 7
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 10
                      Truncate: 5
                      NumFixed: 22
                      OwnScore: [-4.4830 -4.4830 -4.4830 -4.4830 -4.4830 -6.1310 -7.5685 -6.1310 -11.4536 -7.5685]
                   OwnSequence: {1×10 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 7 7 7 7 7 7 7 9 7]
            MeanSequenceLength: 7.2000
               DeficitEditData: [10536×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

10 sequences from 3D structures
Using 10536 random sequences, 0 from an alignment, and 10 from 3D structures
Group  64, IL_15698.3  has acceptance rules AlignmentScore >= -24.4830, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  14.7322
TP   100.00%, TN    96.00%, min    96.00%,  10 3D sequences,     0 alignment sequences, 10495 random sequences,  420 random matches,  7 NTs, cWW-L-R-L-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 420
1 * Deficit + 3 * Core Edit <= 10.2492
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_15991.1'
                     Signature: {'cWW-L-R-L-R-L-R-L-R-L-R-L-R-L-R-L-cWW-L-L'  ''}
                         NumNT: 21
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 17
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 13
                      NumFixed: 70
                      OwnScore: -16.4481
                   OwnSequence: {'GCGUACUGGACCCA*UGGCCGGUC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 23
            MeanSequenceLength: 23
               DeficitEditData: [0×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 0 random sequences, 0 from an alignment, and 1 from 3D structures
No random sequence matches, so essentially no model-specific cutoff imposed
Decreased cutoff to  25.0000 so that it is possible to reject matches
Group  65, IL_15991.1  has acceptance rules AlignmentScore >= -36.4481, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  41.4481
TP   100.00%, TN      NaN%, min   100.00%,   1 3D sequences,     0 alignment sequences,    0 random sequences,    0 random matches, 21 NTs, cWW-L-R-L-R-L-R-L-R-L-R-L-R-L-R-L-cWW-L-L
Sensitivity 100.00%, Specificity    NaN%, Minimum 100.00% using method 12
Number of false positives with core edit > 0 is 0
1 * Deficit + 3 * Core Edit <= 25.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_16218.2'
                     Signature: {'cWW-L-R-L-R-L-cWW'  ''}
                         NumNT: 9
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 3
                      Truncate: 6
                      NumFixed: 26
                      OwnScore: [-6.3399 -6.3399 -7.9257]
                   OwnSequence: {'GAAUC*GUGGC'  'GAAUC*GUGGC'  'CACCC*GUUGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10 10]
            MeanSequenceLength: 10
               DeficitEditData: [10495×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 10495 random sequences, 0 from an alignment, and 3 from 3D structures
Group  66, IL_16218.2  has acceptance rules AlignmentScore >= -26.3399, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  21.3029
TP   100.00%, TN    96.00%, min    96.00%,   3 3D sequences,     0 alignment sequences, 10494 random sequences,  420 random matches,  9 NTs, cWW-L-R-L-R-L-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 420
1 * Deficit + 3 * Core Edit <= 14.9630
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_16386.4'
                     Signature: {'cWW-L-cWW'  ''}
                         NumNT: 5
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 1
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 4
                      Truncate: 4
                      NumFixed: 16
                      OwnScore: [-3.1313 -3.1313 -3.1313 -3.1313]
                   OwnSequence: {'CGG*CG'  'CGG*CG'  'CGG*CG'  'CGG*CG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [5 5 5 5]
            MeanSequenceLength: 5
               DeficitEditData: [4992×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 4992 random sequences, 0 from an alignment, and 4 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group  67, IL_16386.4  has acceptance rules AlignmentScore >= -23.1313, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  12.6313
TP   100.00%, TN    86.54%, min    86.54%,   4 3D sequences,     0 alignment sequences, 4628 random sequences,  623 random matches,  5 NTs, cWW-L-cWW
Sensitivity 100.00%, Specificity  86.54%, Minimum  86.54% using method 11
Number of false positives with core edit > 0 is 623
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_16458.4'
                     Signature: {'cWW-L-R-L-R-cSH-tWH-tHS-cWW'  ''}
                         NumNT: 13
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 15
                        NumBPh: 5
                         NumBR: 1
                  NumInstances: 5
                      Truncate: 8
                      NumFixed: 38
                      OwnScore: [-4.5673 -4.5673 -4.5673 -5.3591 -7.2250]
                   OwnSequence: {'CUAGUAC*GGACCG'  'CUAGUAC*GGACCG'  'CUAGUAC*GGACCG'  'UUAGUAC*GGACCG'  'CCAGUAA*UGACCG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [13 13 13 13 13]
            MeanSequenceLength: 13
               DeficitEditData: [1553×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

5 sequences from 3D structures
Using 1553 random sequences, 0 from an alignment, and 5 from 3D structures
Decreased cutoff from  23.1177 because the cutoff seemed overly generous
Group  68, IL_16458.4  has acceptance rules AlignmentScore >= -24.5673, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.8307
TP   100.00%, TN    98.00%, min    98.00%,   5 3D sequences,     0 alignment sequences, 1553 random sequences,   31 random matches, 13 NTs, cWW-L-R-L-R-cSH-tWH-tHS-cWW
Sensitivity 100.00%, Specificity  98.00%, Minimum  98.00% using method 8
Number of false positives with core edit > 0 is 31
1 * Deficit + 3 * Core Edit <= 21.2634
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_16665.1'
                     Signature: {'cWW-L-R-L-R-L-R-L-cWW'  ''}
                         NumNT: 11
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 7
                      NumFixed: 40
                      OwnScore: -10.3767
                   OwnSequence: {'GAAUUGUUG*CUAAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 14
            MeanSequenceLength: 14
               DeficitEditData: [1871×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 1871 random sequences, 0 from an alignment, and 1 from 3D structures
Group  69, IL_16665.1  has acceptance rules AlignmentScore >= -30.3767, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  29.0404
TP   100.00%, TN    95.78%, min    95.78%,   1 3D sequences,     0 alignment sequences, 1871 random sequences,   79 random matches, 11 NTs, cWW-L-R-L-R-L-R-L-cWW
Sensitivity 100.00%, Specificity  95.78%, Minimum  95.78% using method 6
Number of false positives with core edit > 0 is 79
1 * Deficit + 3 * Core Edit <= 18.6637
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_17069.5'
                     Signature: {'cWW-tSH-tHH-cSS-tWW-tHH-tSS-cWW'  ''}
                         NumNT: 13
                  NumBasepairs: 8
                    Structured: 1
                     NumStacks: 13
                        NumBPh: 4
                         NumBR: 3
                  NumInstances: 5
                      Truncate: 8
                      NumFixed: 34
                      OwnScore: [-7.7917 -9.1498 -8.3025 -9.2578 -12.7005]
                   OwnSequence: {'GGACGUAUA*UGCAAAC'  'GGAGGUAUA*UGCGAAC'  'GGACGUAUA*UGCCAAC'  'UGAUGUAUA*UGCUAAA'  'ACUCGUACG*CGCAAAU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [16 16 16 16 16]
            MeanSequenceLength: 16
               DeficitEditData: [783×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

5 sequences from 3D structures
Using 783 random sequences, 0 from an alignment, and 5 from 3D structures
Decreased cutoff from  24.1783 because the cutoff seemed overly generous
Group  70, IL_17069.5  has acceptance rules AlignmentScore >= -27.7917, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  30.5711
TP   100.00%, TN    97.96%, min    97.96%,   5 3D sequences,     0 alignment sequences,  783 random sequences,   16 random matches, 13 NTs, cWW-tSH-tHH-cSS-tWW-tHH-tSS-cWW
Sensitivity 100.00%, Specificity  97.96%, Minimum  97.96% using method 8
Number of false positives with core edit > 0 is 16
1 * Deficit + 3 * Core Edit <= 22.7794
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_17136.7'
                     Signature: {'cWW-tSH-tHW-tHS-cWW'  ''}
                         NumNT: 10
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 12
                        NumBPh: 2
                         NumBR: 2
                  NumInstances: 14
                      Truncate: 6
                      NumFixed: 18
                      OwnScore: [-6.7435 -6.7435 -7.8046 -7.8046 -6.7737 -6.7737 -7.6569 -7.6516 -6.0194 -6.4991 -7.3327 -7.6213 -6.2638 … ]
                   OwnSequence: {1×14 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10 10 10 10 10 10 10 10 10 10 10 10 10]
            MeanSequenceLength: 10
               DeficitEditData: [4694×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

14 sequences from 3D structures
Using 4694 random sequences, 0 from an alignment, and 14 from 3D structures
Group  71, IL_17136.7  has acceptance rules AlignmentScore >= -26.0194, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.3781
TP   100.00%, TN    95.99%, min    95.99%,  14 3D sequences,     0 alignment sequences, 4669 random sequences,  187 random matches, 10 NTs, cWW-tSH-tHW-tHS-cWW
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 187
1 * Deficit + 3 * Core Edit <= 11.3587
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11
Motif index 12
Motif index 13
Motif index 14


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_17765.1'
                     Signature: {'cWW-tWH-cHW-L-tSS-cSS-cWW-R-L'  ''}
                         NumNT: 14
                  NumBasepairs: 7
                    Structured: 1
                     NumStacks: 11
                        NumBPh: 2
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 11
                      NumFixed: 32
                      OwnScore: -8.3880
                   OwnSequence: {'CUGAGAAAGUC*GGUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 15
            MeanSequenceLength: 15
               DeficitEditData: [569×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 569 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  21.6381 because the cutoff seemed overly generous
Group  72, IL_17765.1  has acceptance rules AlignmentScore >= -28.3880, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  28.3880
TP   100.00%, TN    97.01%, min    97.01%,   1 3D sequences,     0 alignment sequences,  569 random sequences,   17 random matches, 14 NTs, cWW-tWH-cHW-L-tSS-cSS-cWW-R-L
Sensitivity 100.00%, Specificity  97.01%, Minimum  97.01% using method 8
Number of false positives with core edit > 0 is 17
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_17948.2'
                     Signature: {'cWW-L-R-tSH-tHS-cWW'  ''}
                         NumNT: 10
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 13
                      Truncate: 6
                      NumFixed: 18
                      OwnScore: [-6.4166 -6.5078 -6.5078 -6.4166 -7.2468 -7.2468 -7.0260 -6.4597 -6.8206 -8.7309 -6.4597 -10.4852 -18.2694]
                   OwnSequence: {1×13 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10 10 10 10 10 10 10 10 10 10 10 11]
            MeanSequenceLength: 10.0769
               DeficitEditData: [5786×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

13 sequences from 3D structures
Using 5786 random sequences, 0 from an alignment, and 13 from 3D structures
Group  73, IL_17948.2  has acceptance rules AlignmentScore >= -26.4166, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  18.3528
TP   100.00%, TN    96.00%, min    96.00%,  13 3D sequences,     0 alignment sequences, 5779 random sequences,  231 random matches, 10 NTs, cWW-L-R-tSH-tHS-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 231
1 * Deficit + 3 * Core Edit <= 11.9363
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11
Motif index 12
Motif index 13


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_17973.1'
                     Signature: {'cWW-cWW-L-cWW-L-L-R-L-R-L-R-L-R-L-R'  ''}
                         NumNT: 18
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 13
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 16
                      NumFixed: 62
                      OwnScore: -14.1073
                   OwnSequence: {'CAAGCGGGGUGGCACC*GCGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 20
            MeanSequenceLength: 20
               DeficitEditData: [10.1986 5]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 1 random sequences, 0 from an alignment, and 1 from 3D structures
Group  74, IL_17973.1  has acceptance rules AlignmentScore >= -34.1073, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  39.1073
TP   100.00%, TN   100.00%, min   100.00%,   1 3D sequences,     0 alignment sequences,    1 random sequences,    0 random matches, 18 NTs, cWW-cWW-L-cWW-L-L-R-L-R-L-R-L-R-L-R
Sensitivity 100.00%, Specificity 100.00%, Minimum 100.00% using method 1
Number of false positives with core edit > 0 is 0
1 * Deficit + 3 * Core Edit <= 25.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_18354.1'
                     Signature: {'cWW-L-cWW-L-L-R-L-R-L-R'  ''}
                         NumNT: 12
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 11
                      NumFixed: 44
                      OwnScore: [-10.7345 -11.4280]
                   OwnSequence: {'GGAGCGCUGC*GC'  'GGAGCUAAGCU*AC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [12 13]
            MeanSequenceLength: 12.5000
               DeficitEditData: [7028×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 7028 random sequences, 0 from an alignment, and 2 from 3D structures
Group  75, IL_18354.1  has acceptance rules AlignmentScore >= -30.7345, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.9398
TP   100.00%, TN    95.97%, min    95.97%,   2 3D sequences,     0 alignment sequences, 7028 random sequences,  283 random matches, 12 NTs, cWW-L-cWW-L-L-R-L-R-L-R
Sensitivity 100.00%, Specificity  95.97%, Minimum  95.97% using method 6
Number of false positives with core edit > 0 is 283
1 * Deficit + 3 * Core Edit <= 16.2053
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_18472.4'
                     Signature: {'cWW-tSW-R-L-R-L-R-cWW'  ''}
                         NumNT: 11
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 3
                      Truncate: 7
                      NumFixed: 34
                      OwnScore: [-6.6035 -5.4461 -5.4461]
                   OwnSequence: {'GGUCCC*GAAAC'  'GGAACC*GAAAC'  'GGAACC*GAAAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11 11]
            MeanSequenceLength: 11
               DeficitEditData: [5204×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 5204 random sequences, 0 from an alignment, and 3 from 3D structures
Group  76, IL_18472.4  has acceptance rules AlignmentScore >= -25.4461, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  22.7694
TP   100.00%, TN    96.00%, min    96.00%,   3 3D sequences,     0 alignment sequences, 5204 random sequences,  208 random matches, 11 NTs, cWW-tSW-R-L-R-L-R-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 208
1 * Deficit + 3 * Core Edit <= 17.3233
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_18487.1'
                     Signature: {'cWW-L-R-L-R-L-R-L-cWW-cWW'  ''}
                         NumNT: 13
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 8
                      NumFixed: 44
                      OwnScore: [-5.6423 -5.6423]
                   OwnSequence: {'GAAAGCA*UUAAGC'  'GAAAGCA*UUAAGC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [13 13]
            MeanSequenceLength: 13
               DeficitEditData: [2293×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 2293 random sequences, 0 from an alignment, and 2 from 3D structures
Decreased cutoff from  20.2566 because the cutoff seemed overly generous
Group  77, IL_18487.1  has acceptance rules AlignmentScore >= -25.6423, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.6423
TP   100.00%, TN    96.42%, min    96.42%,   2 3D sequences,     0 alignment sequences, 2293 random sequences,   82 random matches, 13 NTs, cWW-L-R-L-R-L-R-L-cWW-cWW
Sensitivity 100.00%, Specificity  96.42%, Minimum  96.42% using method 8
Number of false positives with core edit > 0 is 82
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_19048.1'
                     Signature: {'cWW-L-R-L-R-L-cSH-L-R-cWW-cWW'  ''}
                         NumNT: 14
                  NumBasepairs: 7
                    Structured: 1
                     NumStacks: 12
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 8
                      NumFixed: 34
                      OwnScore: -8.1859
                   OwnSequence: {'AGGUCACA*UUAAGGU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 15
            MeanSequenceLength: 15
               DeficitEditData: [261×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 261 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  23.6165 because the cutoff seemed overly generous
Group  78, IL_19048.1  has acceptance rules AlignmentScore >= -28.1859, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  30.5973
TP   100.00%, TN    98.08%, min    98.08%,   1 3D sequences,     0 alignment sequences,  261 random sequences,    5 random matches, 14 NTs, cWW-L-R-L-R-L-cSH-L-R-cWW-cWW
Sensitivity 100.00%, Specificity  98.08%, Minimum  98.08% using method 8
Number of false positives with core edit > 0 is 5
1 * Deficit + 3 * Core Edit <= 22.4114
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_19102.1'
                     Signature: {'cWW-L-R-L-cWW'  ''}
                         NumNT: 7
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 5
                      NumFixed: 18
                      OwnScore: [-6.3604 -7.6734]
                   OwnSequence: {'UAUAU*AGG'  'CCCAG*CAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8]
            MeanSequenceLength: 8
               DeficitEditData: [13643×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 13643 random sequences, 0 from an alignment, and 2 from 3D structures
Group  79, IL_19102.1  has acceptance rules AlignmentScore >= -26.3604, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.5685
TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 13637 random sequences,  545 random matches,  7 NTs, cWW-L-R-L-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 545
1 * Deficit + 3 * Core Edit <= 10.2081
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_19516.1'
                     Signature: {'cWW-L-R-L-R-L-cWW-L-cWW-L-L-L-R-L-R'  ''}
                         NumNT: 18
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 12
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 14
                      NumFixed: 62
                      OwnScore: -13.3269
                   OwnSequence: {'GGGGACCUACCCAC*GGAAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 19
            MeanSequenceLength: 19
               DeficitEditData: [20×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 20 random sequences, 0 from an alignment, and 1 from 3D structures
Group  80, IL_19516.1  has acceptance rules AlignmentScore >= -33.3269, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  38.3269
TP   100.00%, TN    75.00%, min    75.00%,   1 3D sequences,     0 alignment sequences,   20 random sequences,    5 random matches, 18 NTs, cWW-L-R-L-R-L-cWW-L-cWW-L-L-L-R-L-R
Sensitivity 100.00%, Specificity  75.00%, Minimum  75.00% using method 1
Number of false positives with core edit > 0 is 5
1 * Deficit + 3 * Core Edit <= 25.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_19668.1'
                     Signature: {'cWW-cWW-L-cWW-L'  ''}
                         NumNT: 8
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 6
                      NumFixed: 22
                      OwnScore: [-7.6625 -7.6632]
                   OwnSequence: {'AGAUGC*GAU'  'AAGGAA*UGU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9]
            MeanSequenceLength: 9
               DeficitEditData: [19669×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 19669 random sequences, 0 from an alignment, and 2 from 3D structures
Group  81, IL_19668.1  has acceptance rules AlignmentScore >= -27.6625, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  19.1308
TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 19666 random sequences,  787 random matches,  8 NTs, cWW-cWW-L-cWW-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 787
1 * Deficit + 3 * Core Edit <= 11.4683
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_19852.1'
                     Signature: {'cWW-tWH-cWW-cWH-cWH-cWH'  ''}
                         NumNT: 11
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 10
                      NumFixed: 28
                      OwnScore: -6.2429
                   OwnSequence: {'AGGUGGGUGGU*AU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 13
            MeanSequenceLength: 13
               DeficitEditData: [957×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 957 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  21.9455 because the cutoff seemed overly generous
Group  82, IL_19852.1  has acceptance rules AlignmentScore >= -26.2429, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.9603
TP   100.00%, TN    98.01%, min    98.01%,   1 3D sequences,     0 alignment sequences,  957 random sequences,   19 random matches, 11 NTs, cWW-tWH-cWW-cWH-cWH-cWH
Sensitivity 100.00%, Specificity  98.01%, Minimum  98.01% using method 8
Number of false positives with core edit > 0 is 19
1 * Deficit + 3 * Core Edit <= 20.7174
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_19897.3'
                     Signature: {'cWW-L-cWW-L-L-tWH-R-L'  ''}
                         NumNT: 11
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 10
                      NumFixed: 34
                      OwnScore: [-6.0474 -6.0474]
                   OwnSequence: {'CCAAUCGUA*UG'  'CCAAUCGUA*UG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11]
            MeanSequenceLength: 11
               DeficitEditData: [4766×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 4766 random sequences, 0 from an alignment, and 2 from 3D structures
Group  83, IL_19897.3  has acceptance rules AlignmentScore >= -26.0474, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.3093
TP   100.00%, TN    95.99%, min    95.99%,   2 3D sequences,     0 alignment sequences, 4766 random sequences,  191 random matches, 11 NTs, cWW-L-cWW-L-L-tWH-R-L
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 191
1 * Deficit + 3 * Core Edit <= 19.2619
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_20031.1'
                     Signature: {'cWW-L-cWW-L'  ''}
                         NumNT: 6
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 5
                      NumFixed: 20
                      OwnScore: [-6.6710 -6.6705]
                   OwnSequence: {'CCCUU*AG'  'GGGCG*CC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 7]
            MeanSequenceLength: 7
               DeficitEditData: [14943×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 14943 random sequences, 0 from an alignment, and 2 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group  84, IL_20031.1  has acceptance rules AlignmentScore >= -26.6705, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.1705
TP   100.00%, TN    89.24%, min    89.24%,   2 3D sequences,     0 alignment sequences, 14922 random sequences, 1605 random matches,  6 NTs, cWW-L-cWW-L
Sensitivity 100.00%, Specificity  89.24%, Minimum  89.24% using method 11
Number of false positives with core edit > 0 is 1605
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_20047.1'
                     Signature: {'cWW-tSH-tWH-cSH-cHW-cWH-cWW-cWW'  ''}
                         NumNT: 11
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 2
                         NumBR: 2
                  NumInstances: 2
                      Truncate: 7
                      NumFixed: 22
                      OwnScore: [-6.5682 -6.5687]
                   OwnSequence: {'UGUUGACG*CGAUGG'  'UGUUGACA*UGAUGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [14 14]
            MeanSequenceLength: 14
               DeficitEditData: [1489×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 1489 random sequences, 0 from an alignment, and 2 from 3D structures
Decreased cutoff from  23.0415 because the cutoff seemed overly generous
Group  85, IL_20047.1  has acceptance rules AlignmentScore >= -26.5682, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  27.5704
TP   100.00%, TN    97.99%, min    97.99%,   2 3D sequences,     0 alignment sequences, 1489 random sequences,   30 random matches, 11 NTs, cWW-tSH-tWH-cSH-cHW-cWH-cWW-cWW
Sensitivity 100.00%, Specificity  97.99%, Minimum  97.99% using method 8
Number of false positives with core edit > 0 is 30
1 * Deficit + 3 * Core Edit <= 21.0022
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_20245.1'
                     Signature: {'cWW-L-R-L-R-L-R-L-R-L-R-L-R-L-cWW-L-L-R-L'  ''}
                         NumNT: 18
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 13
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 11
                      NumFixed: 64
                      OwnScore: -18.0765
                   OwnSequence: {'GAUGUGUAGGAUAGGUG*CACCCUUU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 25
            MeanSequenceLength: 25
               DeficitEditData: [0×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 0 random sequences, 0 from an alignment, and 1 from 3D structures
No random sequence matches, so essentially no model-specific cutoff imposed
Decreased cutoff to  25.0000 so that it is possible to reject matches
Group  86, IL_20245.1  has acceptance rules AlignmentScore >= -38.0765, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  43.0765
TP   100.00%, TN      NaN%, min   100.00%,   1 3D sequences,     0 alignment sequences,    0 random sequences,    0 random matches, 18 NTs, cWW-L-R-L-R-L-R-L-R-L-R-L-R-L-cWW-L-L-R-L
Sensitivity 100.00%, Specificity    NaN%, Minimum 100.00% using method 12
Number of false positives with core edit > 0 is 0
1 * Deficit + 3 * Core Edit <= 25.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_20463.1'
                     Signature: {'cWW-tSH-tHW-cSH-tHH-cWH-L-R-cWW-L-L-R'  ''}
                         NumNT: 18
                  NumBasepairs: 7
                    Structured: 1
                     NumStacks: 16
                        NumBPh: 4
                         NumBR: 2
                  NumInstances: 1
                      Truncate: 12
                      NumFixed: 42
                      OwnScore: -9.8739
                   OwnSequence: {'UGAAGCAACGC*GAAGUAA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 18
            MeanSequenceLength: 18
               DeficitEditData: [61×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 61 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  23.9602 because the cutoff seemed overly generous
Group  87, IL_20463.1  has acceptance rules AlignmentScore >= -29.8739, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  29.8739
TP   100.00%, TN    96.72%, min    96.72%,   1 3D sequences,     0 alignment sequences,   61 random sequences,    2 random matches, 18 NTs, cWW-tSH-tHW-cSH-tHH-cWH-L-R-cWW-L-L-R
Sensitivity 100.00%, Specificity  96.72%, Minimum  96.72% using method 8
Number of false positives with core edit > 0 is 2
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_21001.1'
                     Signature: {'cWW-L-R-tHW-L-cWW'  ''}
                         NumNT: 9
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 3
                      Truncate: 6
                      NumFixed: 32
                      OwnScore: [-5.7383 -5.7383 -7.7282]
                   OwnSequence: {'CGAAG*UUUUUG'  'CGAAG*UUUUUG'  'CGAAU*AUUAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11 10]
            MeanSequenceLength: 10.6667
               DeficitEditData: [10825×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 10825 random sequences, 0 from an alignment, and 3 from 3D structures
Group  88, IL_21001.1  has acceptance rules AlignmentScore >= -25.7383, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  21.8434
TP   100.00%, TN    96.00%, min    96.00%,   3 3D sequences,     0 alignment sequences, 10821 random sequences,  433 random matches,  9 NTs, cWW-L-R-tHW-L-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 433
1 * Deficit + 3 * Core Edit <= 16.1051
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_21173.1'
                     Signature: {'cWW-L-cWW-L-L-R-L-R-L'  ''}
                         NumNT: 11
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 10
                      NumFixed: 40
                      OwnScore: [-5.3948 -5.3948]
                   OwnSequence: {'GUGGAACCC*GC'  'GUGGAACCC*GC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11]
            MeanSequenceLength: 11
               DeficitEditData: [5373×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 5373 random sequences, 0 from an alignment, and 2 from 3D structures
Group  89, IL_21173.1  has acceptance rules AlignmentScore >= -25.3948, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  23.9509
TP   100.00%, TN    95.79%, min    95.79%,   2 3D sequences,     0 alignment sequences, 5373 random sequences,  226 random matches, 11 NTs, cWW-L-cWW-L-L-R-L-R-L
Sensitivity 100.00%, Specificity  95.79%, Minimum  95.79% using method 6
Number of false positives with core edit > 0 is 226
1 * Deficit + 3 * Core Edit <= 18.5561
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_21200.1'
                     Signature: {'cWW-tSH-tHW-L-cWW-L'  ''}
                         NumNT: 10
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 6
                      Truncate: 7
                      NumFixed: 24
                      OwnScore: [-7.1674 -6.6767 -6.3201 -6.6566 -6.3402 -6.3402]
                   OwnSequence: {'CAAGUG*CUAG'  'CGAGCG*CUAG'  'CAAGAG*CUAG'  'CAAGCG*CUAG'  'CGAGAG*CUAG'  'CGAGAG*CUAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10 10 10 10 10]
            MeanSequenceLength: 10
               DeficitEditData: [9825×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

6 sequences from 3D structures
Using 9825 random sequences, 0 from an alignment, and 6 from 3D structures
Group  90, IL_21200.1  has acceptance rules AlignmentScore >= -26.3201, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  21.3127
TP   100.00%, TN    96.00%, min    96.00%,   6 3D sequences,     0 alignment sequences, 9823 random sequences,  393 random matches, 10 NTs, cWW-tSH-tHW-L-cWW-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 393
1 * Deficit + 3 * Core Edit <= 14.9926
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_21630.1'
                     Signature: {'cWW-L-R-L-R-L-R-cSH-R-tWH-R-cWW-cWW'  ''}
                         NumNT: 17
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 12
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 10
                      NumFixed: 60
                      OwnScore: -11.6160
                   OwnSequence: {'GAGCCCAAC*GGCUAGAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 17
            MeanSequenceLength: 17
               DeficitEditData: [223×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 223 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  21.9437 because the cutoff seemed overly generous
Group  91, IL_21630.1  has acceptance rules AlignmentScore >= -31.6160, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  31.6160
TP   100.00%, TN    97.76%, min    97.76%,   1 3D sequences,     0 alignment sequences,  223 random sequences,    5 random matches, 17 NTs, cWW-L-R-L-R-L-R-cSH-R-tWH-R-cWW-cWW
Sensitivity 100.00%, Specificity  97.76%, Minimum  97.76% using method 8
Number of false positives with core edit > 0 is 5
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_21667.1'
                     Signature: {'cWW-tSH-L-R-L-cWW'  ''}
                         NumNT: 11
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 2
                      Truncate: 7
                      NumFixed: 34
                      OwnScore: [-6.8759 -6.8759]
                   OwnSequence: {'UAUAAG*UGAAA'  'UAUAAG*UGAAA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11]
            MeanSequenceLength: 11
               DeficitEditData: [9024×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 9024 random sequences, 0 from an alignment, and 2 from 3D structures
Group  92, IL_21667.1  has acceptance rules AlignmentScore >= -26.8759, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  23.0911
TP   100.00%, TN    95.91%, min    95.91%,   2 3D sequences,     0 alignment sequences, 9023 random sequences,  369 random matches, 11 NTs, cWW-tSH-L-R-L-cWW
Sensitivity 100.00%, Specificity  95.91%, Minimum  95.91% using method 6
Number of false positives with core edit > 0 is 369
1 * Deficit + 3 * Core Edit <= 16.2152
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_22373.1'
                     Signature: {'cWW-L-R-cSH-cSH-cWW'  ''}
                         NumNT: 8
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 4
                      Truncate: 6
                      NumFixed: 24
                      OwnScore: [-3.5769 -3.5769 -3.5769 -3.5769]
                   OwnSequence: {'GGUUC*GUC'  'GGUUC*GUC'  'GGUUC*GUC'  'GGUUC*GUC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8 8 8]
            MeanSequenceLength: 8
               DeficitEditData: [3671×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 3671 random sequences, 0 from an alignment, and 4 from 3D structures
Group  93, IL_22373.1  has acceptance rules AlignmentScore >= -23.5769, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.9535
TP   100.00%, TN    95.96%, min    95.96%,   4 3D sequences,     0 alignment sequences, 3665 random sequences,  148 random matches,  8 NTs, cWW-L-R-cSH-cSH-cWW
Sensitivity 100.00%, Specificity  95.96%, Minimum  95.96% using method 6
Number of false positives with core edit > 0 is 148
1 * Deficit + 3 * Core Edit <= 14.3765
Motif index 1
Motif index 2
Motif index 3
Motif index 4


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_22551.4'
                     Signature: {'cWW-L-cWW-L'  ''}
                         NumNT: 6
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 9
                      Truncate: 5
                      NumFixed: 20
                      OwnScore: [-4.1441 -4.1441 -4.1441 -3.9495 -3.9495 -3.9495 -3.9495 -6.8589 -9.8788]
                   OwnSequence: {'GCAU*GC'  'GCAU*GC'  'GCAU*GC'  'GCAC*GC'  'GCAC*GC'  'GCAC*GC'  'GCAC*GC'  'GUUA*UC'  'AUCUG*CU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 6 6 6 6 6 6 7]
            MeanSequenceLength: 6.1111
               DeficitEditData: [9173×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

9 sequences from 3D structures
Using 9173 random sequences, 0 from an alignment, and 9 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group  94, IL_22551.4  has acceptance rules AlignmentScore >= -23.9495, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.4495
TP   100.00%, TN    87.34%, min    87.34%,   9 3D sequences,     0 alignment sequences, 9075 random sequences, 1149 random matches,  6 NTs, cWW-L-cWW-L
Sensitivity 100.00%, Specificity  87.34%, Minimum  87.34% using method 11
Number of false positives with core edit > 0 is 1149
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_22564.1'
                     Signature: {'cWW-L-R-L-R-L-cWW'  ''}
                         NumNT: 9
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 6
                      NumFixed: 34
                      OwnScore: [-11.0598 -9.5033]
                   OwnSequence: {'GUAUAAGC*GAAAUC'  'GUCUAAC*GUAAUC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [14 13]
            MeanSequenceLength: 13.5000
               DeficitEditData: [3923×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 3923 random sequences, 0 from an alignment, and 2 from 3D structures
Group  95, IL_22564.1  has acceptance rules AlignmentScore >= -29.5033, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.6781
TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 3923 random sequences,  157 random matches,  9 NTs, cWW-L-R-L-R-L-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 157
1 * Deficit + 3 * Core Edit <= 17.1748
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_22829.2'
                     Signature: {'cWW-L-tHS-L-R-L-cWW-L'  ''}
                         NumNT: 11
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 3
                      Truncate: 8
                      NumFixed: 28
                      OwnScore: [-6.8665 -6.8665 -12.6477]
                   OwnSequence: {'AAUAAUG*CUAU'  'AAUAAUG*CUAU'  'GGGGUGC*GUCC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11 11]
            MeanSequenceLength: 11
               DeficitEditData: [6699×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 6699 random sequences, 0 from an alignment, and 3 from 3D structures
Group  96, IL_22829.2  has acceptance rules AlignmentScore >= -26.8665, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.5257
TP   100.00%, TN    96.00%, min    96.00%,   3 3D sequences,     0 alignment sequences, 6698 random sequences,  268 random matches, 11 NTs, cWW-L-tHS-L-R-L-cWW-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 268
1 * Deficit + 3 * Core Edit <= 17.6592
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_22854.4'
                     Signature: {'cWW-tSH-cWW-tHW-R-L-cWW-L-L-R'  ''}
                         NumNT: 14
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 11
                        NumBPh: 4
                         NumBR: 1
                  NumInstances: 7
                      Truncate: 10
                      NumFixed: 40
                      OwnScore: [-6.5624 -5.2631 -6.0516 -6.5981 -7.3509 -5.9389 -5.9389]
                   OwnSequence: {1×7 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [14 14 14 14 14 14 14]
            MeanSequenceLength: 14
               DeficitEditData: [487×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

7 sequences from 3D structures
Using 487 random sequences, 0 from an alignment, and 7 from 3D structures
Decreased cutoff from  21.5305 because the cutoff seemed overly generous
Group  97, IL_22854.4  has acceptance rules AlignmentScore >= -25.2631, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.2631
TP   100.00%, TN    97.54%, min    97.54%,   7 3D sequences,     0 alignment sequences,  487 random sequences,   12 random matches, 14 NTs, cWW-tSH-cWW-tHW-R-L-cWW-L-L-R
Sensitivity 100.00%, Specificity  97.54%, Minimum  97.54% using method 8
Number of false positives with core edit > 0 is 12
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_23038.1'
                     Signature: {'cWW-L-R-tWH-L-R-L-cWW-cWW'  ''}
                         NumNT: 13
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 13
                        NumBPh: 2
                         NumBR: 1
                  NumInstances: 2
                      Truncate: 8
                      NumFixed: 28
                      OwnScore: [-5.0164 -5.0164]
                   OwnSequence: {'UCUUAUG*UUAUCA'  'UCUUAUG*UUAUCA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [13 13]
            MeanSequenceLength: 13
               DeficitEditData: [449×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 449 random sequences, 0 from an alignment, and 2 from 3D structures
Decreased cutoff from  23.8750 because the cutoff seemed overly generous
Group  98, IL_23038.1  has acceptance rules AlignmentScore >= -25.0164, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.9835
TP   100.00%, TN    98.00%, min    98.00%,   2 3D sequences,     0 alignment sequences,  449 random sequences,    9 random matches, 13 NTs, cWW-L-R-tWH-L-R-L-cWW-cWW
Sensitivity 100.00%, Specificity  98.00%, Minimum  98.00% using method 8
Number of false positives with core edit > 0 is 9
1 * Deficit + 3 * Core Edit <= 21.9671
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_23774.1'
                     Signature: {'cWW-L-R-L-tHS-cWW'  ''}
                         NumNT: 9
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 11
                      Truncate: 6
                      NumFixed: 20
                      OwnScore: [-7.8605 -8.1532 -9.3324 -8.5671 -9.1439 -9.1439 -10.4087 -8.3296 -10.3944 -7.8605 -10.3795]
                   OwnSequence: {1×11 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 9 9 9 9 9 10 10 10 10 10]
            MeanSequenceLength: 9.5455
               DeficitEditData: [10323×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

11 sequences from 3D structures
Using 10323 random sequences, 0 from an alignment, and 11 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group  99, IL_23774.1  has acceptance rules AlignmentScore >= -27.8605, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.3605
TP   100.00%, TN    95.12%, min    95.12%,  11 3D sequences,     0 alignment sequences, 10305 random sequences,  503 random matches,  9 NTs, cWW-L-R-L-tHS-cWW
Sensitivity 100.00%, Specificity  95.12%, Minimum  95.12% using method 11
Number of false positives with core edit > 0 is 503
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_24134.1'
                     Signature: {'cWW-tSS-L-R-L-tHS-L-cWW-L-L'  ''}
                         NumNT: 12
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 2
                         NumBR: 1
                  NumInstances: 3
                      Truncate: 9
                      NumFixed: 34
                      OwnScore: [-4.2755 -4.7863 -4.2755]
                   OwnSequence: {'CGAGAAAC*GGAG'  'CGCGAAAC*GGAG'  'CGAGAAAC*GGAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [12 12 12]
            MeanSequenceLength: 12
               DeficitEditData: [1374×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 1374 random sequences, 0 from an alignment, and 3 from 3D structures
Group 100, IL_24134.1  has acceptance rules AlignmentScore >= -24.2755, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  20.4591
TP   100.00%, TN    95.71%, min    95.71%,   3 3D sequences,     0 alignment sequences, 1374 random sequences,   59 random matches, 12 NTs, cWW-tSS-L-R-L-tHS-L-cWW-L-L
Sensitivity 100.00%, Specificity  95.71%, Minimum  95.71% using method 6
Number of false positives with core edit > 0 is 59
1 * Deficit + 3 * Core Edit <= 16.1836
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_24254.1'
                     Signature: {'cWW-cWW-tHH-cSH-tWH-tHS-cWW'  ''}
                         NumNT: 13
                  NumBasepairs: 7
                    Structured: 1
                     NumStacks: 13
                        NumBPh: 4
                         NumBR: 2
                  NumInstances: 1
                      Truncate: 8
                      NumFixed: 26
                      OwnScore: -5.5592
                   OwnSequence: {'UUAGUAC*GGAAUA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 13
            MeanSequenceLength: 13
               DeficitEditData: [1404×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 1404 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  21.6365 because the cutoff seemed overly generous
Group 101, IL_24254.1  has acceptance rules AlignmentScore >= -25.5592, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.5592
TP   100.00%, TN    97.86%, min    97.86%,   1 3D sequences,     0 alignment sequences, 1404 random sequences,   30 random matches, 13 NTs, cWW-cWW-tHH-cSH-tWH-tHS-cWW
Sensitivity 100.00%, Specificity  97.86%, Minimum  97.86% using method 8
Number of false positives with core edit > 0 is 30
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_24499.1'
                     Signature: {'cWW-cWS-L-R-L-R-cWW-L-cSH-L'  ''}
                         NumNT: 12
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 9
                      NumFixed: 38
                      OwnScore: -7.4797
                   OwnSequence: {'AGAAGCGU*AAUU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 12
            MeanSequenceLength: 12
               DeficitEditData: [4512×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 4512 random sequences, 0 from an alignment, and 1 from 3D structures
Group 102, IL_24499.1  has acceptance rules AlignmentScore >= -27.4797, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.0970
TP   100.00%, TN    96.01%, min    96.01%,   1 3D sequences,     0 alignment sequences, 4512 random sequences,  180 random matches, 12 NTs, cWW-cWS-L-R-L-R-cWW-L-cSH-L
Sensitivity 100.00%, Specificity  96.01%, Minimum  96.01% using method 6
Number of false positives with core edit > 0 is 180
1 * Deficit + 3 * Core Edit <= 18.6173
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_25186.4'
                     Signature: {'cWW-L-R-L-R-L-R-cWW'  ''}
                         NumNT: 10
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 6
                      Truncate: 6
                      NumFixed: 30
                      OwnScore: [-5.7388 -5.7388 -5.7388 -5.7388 -5.7388 -16.0033]
                   OwnSequence: {'GACCC*GACAAC'  'CACCC*GACAAG'  'CACCC*GACAAG'  'GACCC*GACAAC'  'GACCC*GACAAC'  'CUAAG*UGAUGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11 11 11 11 11]
            MeanSequenceLength: 11
               DeficitEditData: [9245×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

6 sequences from 3D structures
Using 9245 random sequences, 0 from an alignment, and 6 from 3D structures
Group 103, IL_25186.4  has acceptance rules AlignmentScore >= -25.7388, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.2436
TP   100.00%, TN    96.00%, min    96.00%,   6 3D sequences,     0 alignment sequences, 9243 random sequences,  370 random matches, 10 NTs, cWW-L-R-L-R-L-R-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 370
1 * Deficit + 3 * Core Edit <= 18.5048
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_25412.1'
                     Signature: {'cWW-L-cWW-L-L'  ''}
                         NumNT: 7
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 2
                  NumInstances: 1
                      Truncate: 6
                      NumFixed: 24
                      OwnScore: -5.2890
                   OwnSequence: {'CAUUUGG*CG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 9
            MeanSequenceLength: 9
               DeficitEditData: [10713×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 10713 random sequences, 0 from an alignment, and 1 from 3D structures
Group 104, IL_25412.1  has acceptance rules AlignmentScore >= -25.2890, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  20.5136
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 10711 random sequences,  428 random matches,  7 NTs, cWW-L-cWW-L-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 428
1 * Deficit + 3 * Core Edit <= 15.2246
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_25463.1'
                     Signature: {'cWW-L-cWW-L-L'  ''}
                         NumNT: 7
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 6
                      NumFixed: 24
                      OwnScore: [-7.6856 -7.6857]
                   OwnSequence: {'CGUAU*AAG'  'ACCACG*CU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8]
            MeanSequenceLength: 8
               DeficitEditData: [19387×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 19387 random sequences, 0 from an alignment, and 2 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 105, IL_25463.1  has acceptance rules AlignmentScore >= -27.6856, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.1856
TP   100.00%, TN    94.40%, min    94.40%,   2 3D sequences,     0 alignment sequences, 19369 random sequences, 1085 random matches,  7 NTs, cWW-L-cWW-L-L
Sensitivity 100.00%, Specificity  94.40%, Minimum  94.40% using method 11
Number of false positives with core edit > 0 is 1085
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_25573.1'
                     Signature: {'cWW-tSW-L-cWW-L-L'  ''}
                         NumNT: 8
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 1
                         NumBR: 3
                  NumInstances: 1
                      Truncate: 7
                      NumFixed: 24
                      OwnScore: -3.6057
                   OwnSequence: {'GGUAAC*GAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 9
            MeanSequenceLength: 9
               DeficitEditData: [6305×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 6305 random sequences, 0 from an alignment, and 1 from 3D structures
Group 106, IL_25573.1  has acceptance rules AlignmentScore >= -23.6057, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.5110
TP   100.00%, TN    95.89%, min    95.89%,   1 3D sequences,     0 alignment sequences, 6299 random sequences,  259 random matches,  8 NTs, cWW-tSW-L-cWW-L-L
Sensitivity 100.00%, Specificity  95.89%, Minimum  95.89% using method 6
Number of false positives with core edit > 0 is 259
1 * Deficit + 3 * Core Edit <= 13.9053
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_25872.4'
                     Signature: {'cWW-cWW-cWH-cWW'  ''}
                         NumNT: 8
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 5
                      Truncate: 5
                      NumFixed: 16
                      OwnScore: [-6.0834 -6.0834 -7.4164 -6.0035 -8.7026]
                   OwnSequence: {'GGGC*GGUAC'  'GGGC*GGUAC'  'CGGG*CGGG'  'GAGA*UGGU'  'AAAC*GCAU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 8 8 8]
            MeanSequenceLength: 8.4000
               DeficitEditData: [7915×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

5 sequences from 3D structures
Using 7915 random sequences, 0 from an alignment, and 5 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 107, IL_25872.4  has acceptance rules AlignmentScore >= -26.0035, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.5035
TP   100.00%, TN    94.57%, min    94.57%,   5 3D sequences,     0 alignment sequences, 7887 random sequences,  428 random matches,  8 NTs, cWW-cWW-cWH-cWW
Sensitivity 100.00%, Specificity  94.57%, Minimum  94.57% using method 11
Number of false positives with core edit > 0 is 428
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_26222.2'
                     Signature: {'cWW-cWS-cSH-tWH-R-L-R-cWW'  ''}
                         NumNT: 9
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 6
                      Truncate: 6
                      NumFixed: 30
                      OwnScore: [-2.1973 -2.1973 -2.1973 -2.1973 -3.8625 -3.8625]
                   OwnSequence: {'GCACU*AAAC'  'GCACU*AAAC'  'GCACU*AAAC'  'GCACU*AAAC'  'GCGAAU*AAAC'  'GCGAAU*AAAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 9 9 10 10]
            MeanSequenceLength: 9.3333
               DeficitEditData: [2101×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

6 sequences from 3D structures
Using 2101 random sequences, 0 from an alignment, and 6 from 3D structures
Group 108, IL_26222.2  has acceptance rules AlignmentScore >= -22.1973, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.5132
TP   100.00%, TN    95.95%, min    95.95%,   6 3D sequences,     0 alignment sequences, 2100 random sequences,   85 random matches,  9 NTs, cWW-cWS-cSH-tWH-R-L-R-cWW
Sensitivity 100.00%, Specificity  95.95%, Minimum  95.95% using method 6
Number of false positives with core edit > 0 is 85
1 * Deficit + 3 * Core Edit <= 15.3158
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_26307.2'
                     Signature: {'cWW-tSH-tHH-cSH-tWH-tHS-cWW'  ''}
                         NumNT: 13
                  NumBasepairs: 7
                    Structured: 1
                     NumStacks: 16
                        NumBPh: 3
                         NumBR: 3
                  NumInstances: 9
                      Truncate: 8
                      NumFixed: 26
                      OwnScore: [-7.8707 -8.0133 -8.1464 -7.6895 -7.6895 -8.7545 -8.5715 -7.7063 -9.2047]
                   OwnSequence: {1×9 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [13 13 13 13 13 13 13 13 13]
            MeanSequenceLength: 13
               DeficitEditData: [2554×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

9 sequences from 3D structures
Using 2554 random sequences, 0 from an alignment, and 9 from 3D structures
Group 109, IL_26307.2  has acceptance rules AlignmentScore >= -27.6895, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.5291
TP   100.00%, TN    96.01%, min    96.01%,   9 3D sequences,     0 alignment sequences, 2554 random sequences,  102 random matches, 13 NTs, cWW-tSH-tHH-cSH-tWH-tHS-cWW
Sensitivity 100.00%, Specificity  96.01%, Minimum  96.01% using method 6
Number of false positives with core edit > 0 is 102
1 * Deficit + 3 * Core Edit <= 18.8396
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_26598.1'
                     Signature: {'cWW-L-cWW-L-L-R-L-R'  ''}
                         NumNT: 10
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 5
                      Truncate: 9
                      NumFixed: 36
                      OwnScore: [-5.4565 -6.1646 -5.4565 -6.1646 -8.1646]
                   OwnSequence: {'GGCGUCCC*GC'  'AGCCUGCC*GU'  'GGCGUCCC*GC'  'AGCCUGCC*GU'  'GGAAACCC*GC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10 10 10 10]
            MeanSequenceLength: 10
               DeficitEditData: [7047×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

5 sequences from 3D structures
Using 7047 random sequences, 0 from an alignment, and 5 from 3D structures
Group 110, IL_26598.1  has acceptance rules AlignmentScore >= -25.4565, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  21.2583
TP   100.00%, TN    96.00%, min    96.00%,   5 3D sequences,     0 alignment sequences, 7047 random sequences,  282 random matches, 10 NTs, cWW-L-cWW-L-L-R-L-R
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 282
1 * Deficit + 3 * Core Edit <= 15.8017
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_26685.1'
                     Signature: {'cWW-L-cWW-L'  ''}
                         NumNT: 6
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 5
                      NumFixed: 20
                      OwnScore: -3.7358
                   OwnSequence: {'UUGAU*GG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 7
            MeanSequenceLength: 7
               DeficitEditData: [9533×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 9533 random sequences, 0 from an alignment, and 1 from 3D structures
Group 111, IL_26685.1  has acceptance rules AlignmentScore >= -23.7358, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.4024
TP   100.00%, TN    95.92%, min    95.92%,   1 3D sequences,     0 alignment sequences, 9512 random sequences,  388 random matches,  6 NTs, cWW-L-cWW-L
Sensitivity 100.00%, Specificity  95.92%, Minimum  95.92% using method 6
Number of false positives with core edit > 0 is 388
1 * Deficit + 3 * Core Edit <= 11.6667
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_26728.3'
                     Signature: {'cWW-cSH-R-cSH-cWW-cWW'  ''}
                         NumNT: 9
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 2
                      Truncate: 6
                      NumFixed: 26
                      OwnScore: [-5.1475 -5.1475]
                   OwnSequence: {'UGUCG*CUGG'  'UGUCG*CUGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9]
            MeanSequenceLength: 9
               DeficitEditData: [4845×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 4845 random sequences, 0 from an alignment, and 2 from 3D structures
Group 112, IL_26728.3  has acceptance rules AlignmentScore >= -25.1475, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  22.6066
TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 4845 random sequences,  194 random matches,  9 NTs, cWW-cSH-R-cSH-cWW-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 194
1 * Deficit + 3 * Core Edit <= 17.4591
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_26793.1'
                     Signature: {'cWW-L-cWW'  ''}
                         NumNT: 5
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 16
                      Truncate: 4
                      NumFixed: 16
                      OwnScore: [-3.4310 -5.3361 -3.4353 -3.7945 -4.2272 -3.4310 -3.4786 -4.2272 -4.2272 -4.2272 -3.4353 -3.4786 -3.4786 … ]
                   OwnSequence: {1×16 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5]
            MeanSequenceLength: 5
               DeficitEditData: [4992×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

16 sequences from 3D structures
Using 4992 random sequences, 0 from an alignment, and 16 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 113, IL_26793.1  has acceptance rules AlignmentScore >= -23.4310, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  12.9310
TP   100.00%, TN    91.83%, min    91.83%,  16 3D sequences,     0 alignment sequences, 4356 random sequences,  356 random matches,  5 NTs, cWW-L-cWW
Sensitivity 100.00%, Specificity  91.83%, Minimum  91.83% using method 11
Number of false positives with core edit > 0 is 356
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11
Motif index 12
Motif index 13
Motif index 14
Motif index 15
Motif index 16


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_27393.10'
                     Signature: {'cWW-L-cWW-L-L-R-L-R'  ''}
                         NumNT: 10
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 3
                      Truncate: 9
                      NumFixed: 36
                      OwnScore: [-5.9535 -5.4427 -5.4427]
                   OwnSequence: {'CUCCCCAC*GG'  'CUACCCAC*GG'  'CUACCCAC*GG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10 10]
            MeanSequenceLength: 10
               DeficitEditData: [7208×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 7208 random sequences, 0 from an alignment, and 3 from 3D structures
Group 114, IL_27393.10 has acceptance rules AlignmentScore >= -25.4427, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  22.7591
TP   100.00%, TN    95.98%, min    95.98%,   3 3D sequences,     0 alignment sequences, 7208 random sequences,  290 random matches, 10 NTs, cWW-L-cWW-L-L-R-L-R
Sensitivity 100.00%, Specificity  95.98%, Minimum  95.98% using method 6
Number of false positives with core edit > 0 is 290
1 * Deficit + 3 * Core Edit <= 17.3164
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_28026.3'
                     Signature: {'cWW-tSH-tWH-cWH-L-tHW-tSS-tHH-cWW'  ''}
                         NumNT: 15
                  NumBasepairs: 8
                    Structured: 1
                     NumStacks: 15
                        NumBPh: 3
                         NumBR: 1
                  NumInstances: 2
                      Truncate: 9
                      NumFixed: 30
                      OwnScore: [-6.8838 -6.5426]
                   OwnSequence: {'GGAAGAAG*UGUAAAC'  'UGAAGAAG*UGUAAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [15 15]
            MeanSequenceLength: 15
               DeficitEditData: [276×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 276 random sequences, 0 from an alignment, and 2 from 3D structures
Decreased cutoff from  21.4074 because the cutoff seemed overly generous
Group 115, IL_28026.3  has acceptance rules AlignmentScore >= -26.5426, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.5426
TP   100.00%, TN    97.83%, min    97.83%,   2 3D sequences,     0 alignment sequences,  276 random sequences,    6 random matches, 15 NTs, cWW-tSH-tWH-cWH-L-tHW-tSS-tHH-cWW
Sensitivity 100.00%, Specificity  97.83%, Minimum  97.83% using method 8
Number of false positives with core edit > 0 is 6
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_28037.2'
                     Signature: {'cWW-cWW-cWW'  ''}
                         NumNT: 6
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 65
                      Truncate: 4
                      NumFixed: 14
                      OwnScore: [-2.7996 -2.7996 -2.7996 -2.9760 -2.7996 -2.7996 -2.7996 -2.9760 -2.7996 -2.7996 -2.7996 -2.9760 -2.7996 … ]
                   OwnSequence: {1×65 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 … ]
            MeanSequenceLength: 6
               DeficitEditData: [4588×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

65 sequences from 3D structures
Using 4588 random sequences, 0 from an alignment, and 65 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 116, IL_28037.2  has acceptance rules AlignmentScore >= -22.7996, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  12.2996
TP   100.00%, TN    89.89%, min    89.89%,  65 3D sequences,     0 alignment sequences, 4421 random sequences,  447 random matches,  6 NTs, cWW-cWW-cWW
Sensitivity 100.00%, Specificity  89.89%, Minimum  89.89% using method 11
Number of false positives with core edit > 0 is 447
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11
Motif index 12
Motif index 13
Motif index 14
Motif index 15
Motif index 16
Motif index 17
Motif index 18
Motif index 19
Motif index 20
Motif index 21
Motif index 22
Motif index 23
Motif index 24
Motif index 25
Motif index 26
Motif index 27
Motif index 28
Motif index 29
Motif index 30
Motif index 31
Motif index 32
Motif index 33
Motif index 34
Motif index 35
Motif index 36
Motif index 37
Motif index 38
Motif index 39
Motif index 40
Motif index 41
Motif index 42
Motif index 43
Motif index 44
Motif index 45
Motif index 46
Motif index 47
Motif index 48
Motif index 49
Motif index 50
Motif index 51
Motif index 52
Motif index 53
Motif index 54
Motif index 55
Motif index 56
Motif index 57
Motif index 58
Motif index 59
Motif index 60
Motif index 61
Motif index 62
Motif index 63
Motif index 64
Motif index 65


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_28304.1'
                     Signature: {'cWW-R-L-R-L-R-L-R-L-L-L-cWW-cWW'  ''}
                         NumNT: 16
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 13
                        NumBPh: 1
                         NumBR: 2
                  NumInstances: 1
                      Truncate: 10
                      NumFixed: 48
                      OwnScore: -10.5071
                   OwnSequence: {'AUAAGGAUUG*CUUGAUUU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 18
            MeanSequenceLength: 18
               DeficitEditData: [64×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 64 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  22.0862 because the cutoff seemed overly generous
Group 117, IL_28304.1  has acceptance rules AlignmentScore >= -30.5071, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  31.5042
TP   100.00%, TN    98.44%, min    98.44%,   1 3D sequences,     0 alignment sequences,   64 random sequences,    1 random matches, 16 NTs, cWW-R-L-R-L-R-L-R-L-L-L-cWW-cWW
Sensitivity 100.00%, Specificity  98.44%, Minimum  98.44% using method 8
Number of false positives with core edit > 0 is 1
1 * Deficit + 3 * Core Edit <= 20.9971
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_28564.1'
                     Signature: {'cWW-L-R-L-cWW'  ''}
                         NumNT: 7
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 5
                      NumFixed: 18
                      OwnScore: -4.7743
                   OwnSequence: {'UAAA*UCUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 8
            MeanSequenceLength: 8
               DeficitEditData: [9354×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 9354 random sequences, 0 from an alignment, and 1 from 3D structures
Group 118, IL_28564.1  has acceptance rules AlignmentScore >= -24.7743, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.1469
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 9347 random sequences,  374 random matches,  7 NTs, cWW-L-R-L-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 374
1 * Deficit + 3 * Core Edit <= 12.3726
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_28788.1'
                     Signature: {'cWW-L-R-cWW'  ''}
                         NumNT: 6
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 4
                      NumFixed: 20
                      OwnScore: -5.6470
                   OwnSequence: {'GGA*UCGAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 8
            MeanSequenceLength: 8
               DeficitEditData: [15811×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 15811 random sequences, 0 from an alignment, and 1 from 3D structures
Group 119, IL_28788.1  has acceptance rules AlignmentScore >= -25.6470, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.5143
TP   100.00%, TN    95.84%, min    95.84%,   1 3D sequences,     0 alignment sequences, 15807 random sequences,  657 random matches,  6 NTs, cWW-L-R-cWW
Sensitivity 100.00%, Specificity  95.84%, Minimum  95.84% using method 6
Number of false positives with core edit > 0 is 657
1 * Deficit + 3 * Core Edit <= 10.8672
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_29198.2'
                     Signature: {'cWW-cWW-L-R-cSH-R-tWH-tHS-cWW'  ''}
                         NumNT: 14
                  NumBasepairs: 7
                    Structured: 1
                     NumStacks: 14
                        NumBPh: 1
                         NumBR: 2
                  NumInstances: 4
                      Truncate: 8
                      NumFixed: 30
                      OwnScore: [-7.5051 -7.5051 -8.4915 -8.5192]
                   OwnSequence: {'GAGGUAA*UAAAUAU'  'GAGGUAA*UAAAUAU'  'GAGGUAG*CGAAUGC'  'GGGGUAG*CGAAUAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [14 14 14 14]
            MeanSequenceLength: 14
               DeficitEditData: [1852×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 1852 random sequences, 0 from an alignment, and 4 from 3D structures
Decreased cutoff from  20.6510 because the cutoff seemed overly generous
Group 120, IL_29198.2  has acceptance rules AlignmentScore >= -27.5051, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  27.5051
TP   100.00%, TN    96.71%, min    96.71%,   4 3D sequences,     0 alignment sequences, 1852 random sequences,   61 random matches, 14 NTs, cWW-cWW-L-R-cSH-R-tWH-tHS-cWW
Sensitivity 100.00%, Specificity  96.71%, Minimum  96.71% using method 8
Number of false positives with core edit > 0 is 61
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1
Motif index 2
Motif index 3
Motif index 4


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_29223.1'
                     Signature: {'cWW-L-R-L-cWW-cWW-cWW'  ''}
                         NumNT: 11
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 7
                      NumFixed: 22
                      OwnScore: [-6.2659 -6.2659]
                   OwnSequence: {'UUAUUU*AUUCA'  'UUAUUU*AUUCA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11]
            MeanSequenceLength: 11
               DeficitEditData: [3562×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 3562 random sequences, 0 from an alignment, and 2 from 3D structures
Decreased cutoff from  20.4193 because the cutoff seemed overly generous
Group 121, IL_29223.1  has acceptance rules AlignmentScore >= -26.2659, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.2659
TP   100.00%, TN    96.46%, min    96.46%,   2 3D sequences,     0 alignment sequences, 3562 random sequences,  126 random matches, 11 NTs, cWW-L-R-L-cWW-cWW-cWW
Sensitivity 100.00%, Specificity  96.46%, Minimum  96.46% using method 8
Number of false positives with core edit > 0 is 126
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_29346.2'
                     Signature: {'cWW-L-cWW-L-L'  ''}
                         NumNT: 7
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 3
                      Truncate: 6
                      NumFixed: 24
                      OwnScore: [-4.3837 -4.3837 -8.8592]
                   OwnSequence: {'GGGAG*UC'  'GGGAG*UC'  'CGAUUG*CG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 7 8]
            MeanSequenceLength: 7.3333
               DeficitEditData: [12394×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 12394 random sequences, 0 from an alignment, and 3 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 122, IL_29346.2  has acceptance rules AlignmentScore >= -24.3837, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.8837
TP   100.00%, TN    95.61%, min    95.61%,   3 3D sequences,     0 alignment sequences, 12369 random sequences,  543 random matches,  7 NTs, cWW-L-cWW-L-L
Sensitivity 100.00%, Specificity  95.61%, Minimum  95.61% using method 11
Number of false positives with core edit > 0 is 543
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_29357.1'
                     Signature: {'cWW-L-R-L-R-cWH-tHW-cSH-cWW-L-L-cWW-R-R'  ''}
                         NumNT: 18
                  NumBasepairs: 11
                    Structured: 1
                     NumStacks: 16
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 11
                      NumFixed: 42
                      OwnScore: -7.9155
                   OwnSequence: {'CCCUUGGCAGC*GAUACCAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 19
            MeanSequenceLength: 19
               DeficitEditData: [13.6854 5]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 1 random sequences, 0 from an alignment, and 1 from 3D structures
Group 123, IL_29357.1  has acceptance rules AlignmentScore >= -27.9155, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  32.9155
TP   100.00%, TN   100.00%, min   100.00%,   1 3D sequences,     0 alignment sequences,    1 random sequences,    0 random matches, 18 NTs, cWW-L-R-L-R-cWH-tHW-cSH-cWW-L-L-cWW-R-R
Sensitivity 100.00%, Specificity 100.00%, Minimum 100.00% using method 1
Number of false positives with core edit > 0 is 0
1 * Deficit + 3 * Core Edit <= 25.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_29471.1'
                     Signature: {'cWW-cWW-L-tHS-L-cWW'  ''}
                         NumNT: 10
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 7
                      NumFixed: 24
                      OwnScore: -6.2861
                   OwnSequence: {'CUGAAG*CGUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 10
            MeanSequenceLength: 10
               DeficitEditData: [10688×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 10688 random sequences, 0 from an alignment, and 1 from 3D structures
Group 124, IL_29471.1  has acceptance rules AlignmentScore >= -26.2861, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  22.3170
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 10685 random sequences,  427 random matches, 10 NTs, cWW-cWW-L-tHS-L-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 427
1 * Deficit + 3 * Core Edit <= 16.0309
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_29826.1'
                     Signature: {'cWW-tSH-tHH-L-R-L-R-cSH-R-R-L-R-L-R-L-R-L-R-L-cWW'  ''}
                         NumNT: 25
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 17
                        NumBPh: 7
                         NumBR: 2
                  NumInstances: 1
                      Truncate: 14
                      NumFixed: 70
                      OwnScore: -18.0383
                   OwnSequence: {'CCAAAAUGAUCGGGA*UAAUCCUCUGAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 28
            MeanSequenceLength: 28
               DeficitEditData: [0×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 0 random sequences, 0 from an alignment, and 1 from 3D structures
No random sequence matches, so essentially no model-specific cutoff imposed
Decreased cutoff to  25.0000 so that it is possible to reject matches
Group 125, IL_29826.1  has acceptance rules AlignmentScore >= -38.0383, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  43.0383
TP   100.00%, TN      NaN%, min   100.00%,   1 3D sequences,     0 alignment sequences,    0 random sequences,    0 random matches, 25 NTs, cWW-tSH-tHH-L-R-L-R-cSH-R-R-L-R-L-R-L-R-L-R-L-cWW
Sensitivity 100.00%, Specificity    NaN%, Minimum 100.00% using method 12
Number of false positives with core edit > 0 is 0
1 * Deficit + 3 * Core Edit <= 25.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_30441.1'
                     Signature: {'cWW-cSH-tSW-tHW-cWW-L-L-R-L-L-R'  ''}
                         NumNT: 14
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 0
                         NumBR: 2
                  NumInstances: 1
                      Truncate: 12
                      NumFixed: 42
                      OwnScore: -10.9663
                   OwnSequence: {'GUUACGUCCGAAAG*CAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 17
            MeanSequenceLength: 17
               DeficitEditData: [114×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 114 random sequences, 0 from an alignment, and 1 from 3D structures
Group 126, IL_30441.1  has acceptance rules AlignmentScore >= -30.9663, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  30.6789
TP   100.00%, TN    95.61%, min    95.61%,   1 3D sequences,     0 alignment sequences,  114 random sequences,    5 random matches, 14 NTs, cWW-cSH-tSW-tHW-cWW-L-L-R-L-L-R
Sensitivity 100.00%, Specificity  95.61%, Minimum  95.61% using method 6
Number of false positives with core edit > 0 is 5
1 * Deficit + 3 * Core Edit <= 19.7126
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_30730.1'
                     Signature: {'cWW-cSH-L-R-L-cWW-L-R'  ''}
                         NumNT: 9
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 7
                      NumFixed: 34
                      OwnScore: [-5.8665 -5.8665]
                   OwnSequence: {'UUCAACUCG*CUA'  'UUCAACUCG*CUA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [12 12]
            MeanSequenceLength: 12
               DeficitEditData: [2274×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 2274 random sequences, 0 from an alignment, and 2 from 3D structures
Decreased cutoff from  22.0952 because the cutoff seemed overly generous
Group 127, IL_30730.1  has acceptance rules AlignmentScore >= -25.8665, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.1614
TP   100.00%, TN    98.02%, min    98.02%,   2 3D sequences,     0 alignment sequences, 2274 random sequences,   45 random matches,  9 NTs, cWW-cSH-L-R-L-cWW-L-R
Sensitivity 100.00%, Specificity  98.02%, Minimum  98.02% using method 8
Number of false positives with core edit > 0 is 45
1 * Deficit + 3 * Core Edit <= 20.2949
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_31084.1'
                     Signature: {'cWW-L-R-L-R-L-R-L-cWW-L'  ''}
                         NumNT: 12
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 8
                      NumFixed: 44
                      OwnScore: -8.2173
                   OwnSequence: {'UGAACCG*CAAAA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 12
            MeanSequenceLength: 12
               DeficitEditData: [7319×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 7319 random sequences, 0 from an alignment, and 1 from 3D structures
Group 128, IL_31084.1  has acceptance rules AlignmentScore >= -28.2173, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.4899
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 7319 random sequences,  293 random matches, 12 NTs, cWW-L-R-L-R-L-R-L-cWW-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 293
1 * Deficit + 3 * Core Edit <= 17.2726
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_31462.6'
                     Signature: {'cWW-L-cWW'  ''}
                         NumNT: 5
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 130
                      Truncate: 4
                      NumFixed: 16
                      OwnScore: [-3.0552 -2.6149 -3.0552 -3.9639 -2.6149 -2.2676 -4.5193 -3.9639 -2.6166 -2.6149 -3.7814 -3.3004 -3.4239 … ]
                   OwnSequence: {1×130 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 … ]
            MeanSequenceLength: 5
               DeficitEditData: [4415×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

130 sequences from 3D structures
Using 4415 random sequences, 0 from an alignment, and 130 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 129, IL_31462.6  has acceptance rules AlignmentScore >= -22.2676, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  11.7676
TP   100.00%, TN    90.52%, min    90.52%, 130 3D sequences,     0 alignment sequences, 4166 random sequences,  395 random matches,  5 NTs, cWW-L-cWW
Sensitivity 100.00%, Specificity  90.52%, Minimum  90.52% using method 11
Number of false positives with core edit > 0 is 395
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11
Motif index 12
Motif index 13
Motif index 14
Motif index 15
Motif index 16
Motif index 17
Motif index 18
Motif index 19
Motif index 20
Motif index 21
Motif index 22
Motif index 23
Motif index 24
Motif index 25
Motif index 26
Motif index 27
Motif index 28
Motif index 29
Motif index 30
Motif index 31
Motif index 32
Motif index 33
Motif index 34
Motif index 35
Motif index 36
Motif index 37
Motif index 38
Motif index 39
Motif index 40
Motif index 41
Motif index 42
Motif index 43
Motif index 44
Motif index 45
Motif index 46
Motif index 47
Motif index 48
Motif index 49
Motif index 50
Motif index 51
Motif index 52
Motif index 53
Motif index 54
Motif index 55
Motif index 56
Motif index 57
Motif index 58
Motif index 59
Motif index 60
Motif index 61
Motif index 62
Motif index 63
Motif index 64
Motif index 65
Motif index 66
Motif index 67
Motif index 68
Motif index 69
Motif index 70
Motif index 71
Motif index 72
Motif index 73
Motif index 74
Motif index 75
Motif index 76
Motif index 77
Motif index 78
Motif index 79
Motif index 80
Motif index 81
Motif index 82
Motif index 83
Motif index 84
Motif index 85
Motif index 86
Motif index 87
Motif index 88
Motif index 89
Motif index 90
Motif index 91
Motif index 92
Motif index 93
Motif index 94
Motif index 95
Motif index 96
Motif index 97
Motif index 98
Motif index 99
Motif index 100
Motif index 101
Motif index 102
Motif index 103
Motif index 104
Motif index 105
Motif index 106
Motif index 107
Motif index 108
Motif index 109
Motif index 110
Motif index 111
Motif index 112
Motif index 113
Motif index 114
Motif index 115
Motif index 116
Motif index 117
Motif index 118
Motif index 119
Motif index 120
Motif index 121
Motif index 122
Motif index 123
Motif index 124
Motif index 125
Motif index 126
Motif index 127
Motif index 128
Motif index 129
Motif index 130


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_31504.1'
                     Signature: {'cWW-cWW-cWS-tSH-L-tWH-cWW-tSS-tSH-L-R-L'  ''}
                         NumNT: 18
                  NumBasepairs: 10
                    Structured: 1
                     NumStacks: 15
                        NumBPh: 2
                         NumBR: 3
                  NumInstances: 1
                      Truncate: 14
                      NumFixed: 40
                      OwnScore: -9.5589
                   OwnSequence: {'GAGGCGAAAUAGAGC*GUACC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 20
            MeanSequenceLength: 20
               DeficitEditData: [11×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 11 random sequences, 0 from an alignment, and 1 from 3D structures
Group 130, IL_31504.1  has acceptance rules AlignmentScore >= -29.5589, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  34.5589
TP   100.00%, TN    90.91%, min    90.91%,   1 3D sequences,     0 alignment sequences,   11 random sequences,    1 random matches, 18 NTs, cWW-cWW-cWS-tSH-L-tWH-cWW-tSS-tSH-L-R-L
Sensitivity 100.00%, Specificity  90.91%, Minimum  90.91% using method 1
Number of false positives with core edit > 0 is 1
1 * Deficit + 3 * Core Edit <= 25.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_31531.3'
                     Signature: {'cWW-L-R-L-cWW'  ''}
                         NumNT: 7
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 13
                      Truncate: 5
                      NumFixed: 24
                      OwnScore: [-3.4261 -3.4261 -5.3435 -3.4261 -3.4261 -3.4261 -3.4261 -3.4261 -6.6962 -3.4261 -4.3735 -5.8996 -4.3735]
                   OwnSequence: {1×13 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 7 7 7 7 7 7 7 7 7 7 7 7]
            MeanSequenceLength: 7
               DeficitEditData: [8543×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

13 sequences from 3D structures
Using 8543 random sequences, 0 from an alignment, and 13 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 131, IL_31531.3  has acceptance rules AlignmentScore >= -23.4261, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  12.9261
TP   100.00%, TN    94.92%, min    94.92%,  13 3D sequences,     0 alignment sequences, 8402 random sequences,  427 random matches,  7 NTs, cWW-L-R-L-cWW
Sensitivity 100.00%, Specificity  94.92%, Minimum  94.92% using method 11
Number of false positives with core edit > 0 is 427
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11
Motif index 12
Motif index 13


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_31558.1'
                     Signature: {'cWW-L-tHS-L-R-cWW'  ''}
                         NumNT: 9
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 6
                      NumFixed: 26
                      OwnScore: -5.7275
                   OwnSequence: {'CGAAG*UGGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 9
            MeanSequenceLength: 9
               DeficitEditData: [11099×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 11099 random sequences, 0 from an alignment, and 1 from 3D structures
Group 132, IL_31558.1  has acceptance rules AlignmentScore >= -25.7275, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  19.5855
TP   100.00%, TN    95.95%, min    95.95%,   1 3D sequences,     0 alignment sequences, 11098 random sequences,  449 random matches,  9 NTs, cWW-L-tHS-L-R-cWW
Sensitivity 100.00%, Specificity  95.95%, Minimum  95.95% using method 6
Number of false positives with core edit > 0 is 449
1 * Deficit + 3 * Core Edit <= 13.8579
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_31561.1'
                     Signature: {'cWW-L-R-tWH-tWH-L-R-L-cWW'  ''}
                         NumNT: 13
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 11
                        NumBPh: 3
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 8
                      NumFixed: 36
                      OwnScore: -5.5778
                   OwnSequence: {'GACUGAC*GAAACC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 13
            MeanSequenceLength: 13
               DeficitEditData: [2650×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 2650 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  21.5897 because the cutoff seemed overly generous
Group 133, IL_31561.1  has acceptance rules AlignmentScore >= -25.5778, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.5778
TP   100.00%, TN    97.62%, min    97.62%,   1 3D sequences,     0 alignment sequences, 2650 random sequences,   63 random matches, 13 NTs, cWW-L-R-tWH-tWH-L-R-L-cWW
Sensitivity 100.00%, Specificity  97.62%, Minimum  97.62% using method 8
Number of false positives with core edit > 0 is 63
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_31737.3'
                     Signature: {'cWW-L-cWW'  ''}
                         NumNT: 5
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 12
                      Truncate: 4
                      NumFixed: 16
                      OwnScore: [-6.7199 -6.7199 -6.3045 -6.1452 -7.6126 -6.2740 -6.0540 -4.8320 -4.8320 -9.0071 -6.2740 -12.0198]
                   OwnSequence: {1×12 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 5 6 6 7 6 6 6 7 7 8]
            MeanSequenceLength: 6.3333
               DeficitEditData: [10724×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

12 sequences from 3D structures
Using 10724 random sequences, 0 from an alignment, and 12 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 134, IL_31737.3  has acceptance rules AlignmentScore >= -24.8320, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  14.3320
TP   100.00%, TN    80.57%, min    80.57%,  12 3D sequences,     0 alignment sequences, 10284 random sequences, 1998 random matches,  5 NTs, cWW-L-cWW
Sensitivity 100.00%, Specificity  80.57%, Minimum  80.57% using method 11
Number of false positives with core edit > 0 is 1998
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11
Motif index 12


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_31915.1'
                     Signature: {'cWW-L-R-L-R-L-R-L-R-L-R-L-cWW'  ''}
                         NumNT: 15
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 11
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 3
                      Truncate: 9
                      NumFixed: 56
                      OwnScore: [-8.5073 -8.5073 -9.7276]
                   OwnSequence: {'GUUUUUAUC*GUUUUUC'  'GUUUUUAUC*GUUUUUC'  'GUUUUUAC*GGUUUUC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [16 16 15]
            MeanSequenceLength: 15.6667
               DeficitEditData: [190×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 190 random sequences, 0 from an alignment, and 3 from 3D structures
Decreased cutoff from  21.4666 because the cutoff seemed overly generous
Group 135, IL_31915.1  has acceptance rules AlignmentScore >= -28.5073, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  29.6716
TP   100.00%, TN    97.89%, min    97.89%,   3 3D sequences,     0 alignment sequences,  190 random sequences,    4 random matches, 15 NTs, cWW-L-R-L-R-L-R-L-R-L-R-L-cWW
Sensitivity 100.00%, Specificity  97.89%, Minimum  97.89% using method 8
Number of false positives with core edit > 0 is 4
1 * Deficit + 3 * Core Edit <= 21.1643
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_32016.1'
                     Signature: {'cWW-tSH-tSH-tSS-tHS-L-R-cWW'  ''}
                         NumNT: 12
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 3
                         NumBR: 5
                  NumInstances: 1
                      Truncate: 7
                      NumFixed: 30
                      OwnScore: -6.1551
                   OwnSequence: {'UGGAAG*CAGGAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 13
            MeanSequenceLength: 13
               DeficitEditData: [1791×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 1791 random sequences, 0 from an alignment, and 1 from 3D structures
Group 136, IL_32016.1  has acceptance rules AlignmentScore >= -26.1551, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.5461
TP   100.00%, TN    95.98%, min    95.98%,   1 3D sequences,     0 alignment sequences, 1791 random sequences,   72 random matches, 12 NTs, cWW-tSH-tSH-tSS-tHS-L-R-cWW
Sensitivity 100.00%, Specificity  95.98%, Minimum  95.98% using method 6
Number of false positives with core edit > 0 is 72
1 * Deficit + 3 * Core Edit <= 19.3910
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_32056.1'
                     Signature: {'cWW-L-cWW-L-L-tWH-R-L-R-L'  ''}
                         NumNT: 13
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 2
                         NumBR: 1
                  NumInstances: 3
                      Truncate: 12
                      NumFixed: 38
                      OwnScore: [-8.0899 -6.5574 -6.5574]
                   OwnSequence: {'GUGCAGCAUAG*CC'  'GCGUAGGAUAG*CC'  'GCGUAGGAUAG*CC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [13 13 13]
            MeanSequenceLength: 13
               DeficitEditData: [1907×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 1907 random sequences, 0 from an alignment, and 3 from 3D structures
Decreased cutoff from  21.2750 because the cutoff seemed overly generous
Group 137, IL_32056.1  has acceptance rules AlignmentScore >= -26.5574, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.5574
TP   100.00%, TN    97.33%, min    97.33%,   3 3D sequences,     0 alignment sequences, 1907 random sequences,   51 random matches, 13 NTs, cWW-L-cWW-L-L-tWH-R-L-R-L
Sensitivity 100.00%, Specificity  97.33%, Minimum  97.33% using method 8
Number of false positives with core edit > 0 is 51
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_33141.1'
                     Signature: {'cWW-L-R-L-R-L-cWW-L-L'  ''}
                         NumNT: 11
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 8
                      NumFixed: 28
                      OwnScore: -7.0559
                   OwnSequence: {'CCCUUGG*CCAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 11
            MeanSequenceLength: 11
               DeficitEditData: [4584×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 4584 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  20.5934 because the cutoff seemed overly generous
Group 138, IL_33141.1  has acceptance rules AlignmentScore >= -27.0559, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  27.0559
TP   100.00%, TN    96.68%, min    96.68%,   1 3D sequences,     0 alignment sequences, 4584 random sequences,  152 random matches, 11 NTs, cWW-L-R-L-R-L-cWW-L-L
Sensitivity 100.00%, Specificity  96.68%, Minimum  96.68% using method 8
Number of false positives with core edit > 0 is 152
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_33323.1'
                     Signature: {'cWW-L-R-L-cWW-L-L'  ''}
                         NumNT: 9
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 7
                      NumFixed: 24
                      OwnScore: [-8.1135 -6.4717]
                   OwnSequence: {'CCCUUG*CAG'  'CAGAAG*CAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9]
            MeanSequenceLength: 9
               DeficitEditData: [9039×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 9039 random sequences, 0 from an alignment, and 2 from 3D structures
Group 139, IL_33323.1  has acceptance rules AlignmentScore >= -26.4717, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  19.7078
TP   100.00%, TN    96.01%, min    96.01%,   2 3D sequences,     0 alignment sequences, 9037 random sequences,  361 random matches,  9 NTs, cWW-L-R-L-cWW-L-L
Sensitivity 100.00%, Specificity  96.01%, Minimum  96.01% using method 6
Number of false positives with core edit > 0 is 361
1 * Deficit + 3 * Core Edit <= 13.2361
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_33623.1'
                     Signature: {'cWW-L-tHH-L-R-L-cWW-L-R'  ''}
                         NumNT: 12
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 9
                      NumFixed: 32
                      OwnScore: -7.9288
                   OwnSequence: {'CACGGAAG*CUGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 12
            MeanSequenceLength: 12
               DeficitEditData: [5363×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 5363 random sequences, 0 from an alignment, and 1 from 3D structures
Group 140, IL_33623.1  has acceptance rules AlignmentScore >= -27.9288, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  27.3748
TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences, 5363 random sequences,  215 random matches, 12 NTs, cWW-L-tHH-L-R-L-cWW-L-R
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 215
1 * Deficit + 3 * Core Edit <= 19.4461
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_33711.1'
                     Signature: {'cWW-cSH-cWW-L-L-R-L'  ''}
                         NumNT: 9
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 2
                         NumBR: 2
                  NumInstances: 2
                      Truncate: 8
                      NumFixed: 34
                      OwnScore: [-8.0055 -8.0233]
                   OwnSequence: {'AACAUACUC*GU'  'GUCAAUUCG*CC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11]
            MeanSequenceLength: 11
               DeficitEditData: [7603×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 7603 random sequences, 0 from an alignment, and 2 from 3D structures
Group 141, IL_33711.1  has acceptance rules AlignmentScore >= -28.0055, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.4405
TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 7603 random sequences,  304 random matches,  9 NTs, cWW-cSH-cWW-L-L-R-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 304
1 * Deficit + 3 * Core Edit <= 17.4350
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_33761.2'
                     Signature: {'cWW-L-cWW'  ''}
                         NumNT: 5
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 3
                      Truncate: 4
                      NumFixed: 16
                      OwnScore: [-5.3180 -4.3130 -3.7914]
                   OwnSequence: {'UGAC*GG'  'GUC*GC'  'CAC*GG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 5 5]
            MeanSequenceLength: 5.3333
               DeficitEditData: [8664×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 8664 random sequences, 0 from an alignment, and 3 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 142, IL_33761.2  has acceptance rules AlignmentScore >= -23.7914, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.2914
TP   100.00%, TN    83.67%, min    83.67%,   3 3D sequences,     0 alignment sequences, 8011 random sequences, 1308 random matches,  5 NTs, cWW-L-cWW
Sensitivity 100.00%, Specificity  83.67%, Minimum  83.67% using method 11
Number of false positives with core edit > 0 is 1308
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_33886.1'
                     Signature: {'cWW-L-cWW-L-R-L-R-cWW'  ''}
                         NumNT: 11
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 2
                      Truncate: 7
                      NumFixed: 34
                      OwnScore: [-9.9225 -10.9481]
                   OwnSequence: {'CAAUGUG*CGAAG'  'ACCACGG*CUUCU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [12 12]
            MeanSequenceLength: 12
               DeficitEditData: [8505×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 8505 random sequences, 0 from an alignment, and 2 from 3D structures
Group 143, IL_33886.1  has acceptance rules AlignmentScore >= -29.9225, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.5478
TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 8505 random sequences,  340 random matches, 11 NTs, cWW-L-cWW-L-R-L-R-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 340
1 * Deficit + 3 * Core Edit <= 16.6253
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_34470.3'
                     Signature: {'cWW-cSH-cWW-tHH-tWH-tHS-cWW-tSH-R-cWW-L'  ''}
                         NumNT: 17
                  NumBasepairs: 8
                    Structured: 1
                     NumStacks: 19
                        NumBPh: 3
                         NumBR: 2
                  NumInstances: 2
                      Truncate: 10
                      NumFixed: 36
                      OwnScore: [-8.9642 -8.9642]
                   OwnSequence: {'GAUGAGUAG*UGAAAGGC'  'GAUGAGUAG*UGAAAGGC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [17 17]
            MeanSequenceLength: 17
               DeficitEditData: [175×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 175 random sequences, 0 from an alignment, and 2 from 3D structures
Decreased cutoff from  23.5260 because the cutoff seemed overly generous
Group 144, IL_34470.3  has acceptance rules AlignmentScore >= -28.9642, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  28.9642
TP   100.00%, TN    97.71%, min    97.71%,   2 3D sequences,     0 alignment sequences,  175 random sequences,    4 random matches, 17 NTs, cWW-cSH-cWW-tHH-tWH-tHS-cWW-tSH-R-cWW-L
Sensitivity 100.00%, Specificity  97.71%, Minimum  97.71% using method 8
Number of false positives with core edit > 0 is 4
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_34737.1'
                     Signature: {'cWW-L-cHW-L-cWW-L'  ''}
                         NumNT: 9
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 2
                  NumInstances: 1
                      Truncate: 7
                      NumFixed: 26
                      OwnScore: -6.4607
                   OwnSequence: {'CGUAUC*GAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 10
            MeanSequenceLength: 10
               DeficitEditData: [14476×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 14476 random sequences, 0 from an alignment, and 1 from 3D structures
Group 145, IL_34737.1  has acceptance rules AlignmentScore >= -26.4607, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  22.4218
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 14474 random sequences,  579 random matches,  9 NTs, cWW-L-cHW-L-cWW-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 579
1 * Deficit + 3 * Core Edit <= 15.9611
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_34739.3'
                     Signature: {'cWW-tWW-tWW-L-R-L-R-L-cWW-L-L-R-L-R-L-R-L-R'  ''}
                         NumNT: 20
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 12
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 3
                      Truncate: 16
                      NumFixed: 76
                      OwnScore: [-11.3540 -11.3540 -11.3540]
                   OwnSequence: {'GAAACAAUACAGAGAUGAUCA*UUUAC'  'GAAACAAUACAGAGAUGAUCA*UUUAC'  'GAAACAAUACAGAGAUGAUCA*UUUAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [26 26 26]
            MeanSequenceLength: 26
               DeficitEditData: [0×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 0 random sequences, 0 from an alignment, and 3 from 3D structures
No random sequence matches, so essentially no model-specific cutoff imposed
Decreased cutoff to  25.0000 so that it is possible to reject matches
Group 146, IL_34739.3  has acceptance rules AlignmentScore >= -31.3540, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  36.3540
TP   100.00%, TN      NaN%, min   100.00%,   3 3D sequences,     0 alignment sequences,    0 random sequences,    0 random matches, 20 NTs, cWW-tWW-tWW-L-R-L-R-L-cWW-L-L-R-L-R-L-R-L-R
Sensitivity 100.00%, Specificity    NaN%, Minimum 100.00% using method 12
Number of false positives with core edit > 0 is 0
1 * Deficit + 3 * Core Edit <= 25.0000
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_34822.1'
                     Signature: {'cWW-L-R-L-R-L-R-L-R-cWW'  ''}
                         NumNT: 12
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 11
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 7
                      NumFixed: 26
                      OwnScore: [-9.4644 -9.8297]
                   OwnSequence: {'AAAAAU*GCCAAU'  'CCAACU*ACGAACG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [12 13]
            MeanSequenceLength: 12.5000
               DeficitEditData: [5295×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 5295 random sequences, 0 from an alignment, and 2 from 3D structures
Group 147, IL_34822.1  has acceptance rules AlignmentScore >= -29.4644, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.2657
TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 5295 random sequences,  212 random matches, 12 NTs, cWW-L-R-L-R-L-R-L-R-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 212
1 * Deficit + 3 * Core Edit <= 16.8012
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_36516.3'
                     Signature: {'cWW-cWW-cSH-cWW-L'  ''}
                         NumNT: 8
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 7
                      Truncate: 6
                      NumFixed: 22
                      OwnScore: [-6.4012 -6.4012 -6.9116 -6.6599 -6.8320 -7.1720 -6.2663]
                   OwnSequence: {'AAUCU*ACU'  'AAUCU*ACU'  'AAGCU*ACU'  'GGAUC*GAC'  'GGUUC*GAC'  'CAGUG*CAG'  'GAAUG*CGC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8 8 8 8 8 8]
            MeanSequenceLength: 8
               DeficitEditData: [8638×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

7 sequences from 3D structures
Using 8638 random sequences, 0 from an alignment, and 7 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 148, IL_36516.3  has acceptance rules AlignmentScore >= -26.2663, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.7663
TP   100.00%, TN    95.62%, min    95.62%,   7 3D sequences,     0 alignment sequences, 8611 random sequences,  377 random matches,  8 NTs, cWW-cWW-cSH-cWW-L
Sensitivity 100.00%, Specificity  95.62%, Minimum  95.62% using method 11
Number of false positives with core edit > 0 is 377
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_36729.1'
                     Signature: {'cWW-cWW-L-R-L-R-L-R-tWH-R-L-R-L-cWW'  ''}
                         NumNT: 17
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 11
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 10
                      NumFixed: 56
                      OwnScore: -11.8345
                   OwnSequence: {'GAGCCCAAC*GGCUAGAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 17
            MeanSequenceLength: 17
               DeficitEditData: [230×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 230 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  22.4676 because the cutoff seemed overly generous
Group 149, IL_36729.1  has acceptance rules AlignmentScore >= -31.8345, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  31.8345
TP   100.00%, TN    96.96%, min    96.96%,   1 3D sequences,     0 alignment sequences,  230 random sequences,    7 random matches, 17 NTs, cWW-cWW-L-R-L-R-L-R-tWH-R-L-R-L-cWW
Sensitivity 100.00%, Specificity  96.96%, Minimum  96.96% using method 8
Number of false positives with core edit > 0 is 7
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_37015.1'
                     Signature: {'cWW-tSS-tSS-tHH-L-tHS-L-R-cWW-L'  ''}
                         NumNT: 13
                  NumBasepairs: 8
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 0
                         NumBR: 2
                  NumInstances: 1
                      Truncate: 9
                      NumFixed: 34
                      OwnScore: -8.3531
                   OwnSequence: {'CGUUAUAAC*GUAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 14
            MeanSequenceLength: 14
               DeficitEditData: [1176×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 1176 random sequences, 0 from an alignment, and 1 from 3D structures
Group 150, IL_37015.1  has acceptance rules AlignmentScore >= -28.3531, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  27.5965
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 1176 random sequences,   47 random matches, 13 NTs, cWW-tSS-tSS-tHH-L-tHS-L-R-cWW-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 47
1 * Deficit + 3 * Core Edit <= 19.2433
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_37603.1'
                     Signature: {'cWW-L-cWW-L-cWW-L-L'  ''}
                         NumNT: 10
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 8
                      NumFixed: 30
                      OwnScore: -7.6534
                   OwnSequence: {'CAUCUCGC*GAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 11
            MeanSequenceLength: 11
               DeficitEditData: [7580×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 7580 random sequences, 0 from an alignment, and 1 from 3D structures
Group 151, IL_37603.1  has acceptance rules AlignmentScore >= -27.6534, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.7486
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 7580 random sequences,  303 random matches, 10 NTs, cWW-L-cWW-L-cWW-L-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 303
1 * Deficit + 3 * Core Edit <= 19.0952
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_37752.1'
                     Signature: {'cWW-L-R-L-R-tHW-R-L-cWW'  ''}
                         NumNT: 12
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 12
                        NumBPh: 2
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 7
                      NumFixed: 26
                      OwnScore: -7.2318
                   OwnSequence: {'ACUAUACCG*CUGCCU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 15
            MeanSequenceLength: 15
               DeficitEditData: [186×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 186 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  25.5122 because the cutoff seemed overly generous
Group 152, IL_37752.1  has acceptance rules AlignmentScore >= -27.2318, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  31.7043
TP   100.00%, TN    97.85%, min    97.85%,   1 3D sequences,     0 alignment sequences,  186 random sequences,    4 random matches, 12 NTs, cWW-L-R-L-R-tHW-R-L-cWW
Sensitivity 100.00%, Specificity  97.85%, Minimum  97.85% using method 8
Number of false positives with core edit > 0 is 4
1 * Deficit + 3 * Core Edit <= 24.4725
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_38186.6'
                     Signature: {'cWW-L-cWW-L-L-R'  ''}
                         NumNT: 8
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 4
                      Truncate: 7
                      NumFixed: 28
                      OwnScore: [-5.1231 -5.1231 -5.1235 -5.1235]
                   OwnSequence: {'CGUAAAG*CG'  'CGUAAAG*CG'  'GUUAAAA*UC'  'GUUAAAA*UC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 9 9]
            MeanSequenceLength: 9
               DeficitEditData: [10051×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 10051 random sequences, 0 from an alignment, and 4 from 3D structures
Group 153, IL_38186.6  has acceptance rules AlignmentScore >= -25.1231, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.5279
TP   100.00%, TN    95.96%, min    95.96%,   4 3D sequences,     0 alignment sequences, 10047 random sequences,  406 random matches,  8 NTs, cWW-L-cWW-L-L-R
Sensitivity 100.00%, Specificity  95.96%, Minimum  95.96% using method 6
Number of false positives with core edit > 0 is 406
1 * Deficit + 3 * Core Edit <= 12.4048
Motif index 1
Motif index 2
Motif index 3
Motif index 4


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_38394.1'
                     Signature: {'cWW-tWH-cWW-L-L-R-L'  ''}
                         NumNT: 10
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 9
                      NumFixed: 26
                      OwnScore: [-5.4278 -5.4278]
                   OwnSequence: {'CUGAGAAA*UG'  'CUGAGAAA*UG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10]
            MeanSequenceLength: 10
               DeficitEditData: [3828×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 3828 random sequences, 0 from an alignment, and 2 from 3D structures
Group 154, IL_38394.1  has acceptance rules AlignmentScore >= -25.4278, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  20.6659
TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 3828 random sequences,  153 random matches, 10 NTs, cWW-tWH-cWW-L-L-R-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 153
1 * Deficit + 3 * Core Edit <= 15.2382
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_38507.2'
                     Signature: {'cWW-tWH-L-tHS-cWW'  ''}
                         NumNT: 9
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 16
                      Truncate: 6
                      NumFixed: 20
                      OwnScore: [-5.0903 -5.0903 -5.0903 -5.0903 -7.5148 -7.4926 -7.4926 -5.0903 -8.5595 -6.1120 -5.0903 -8.2090 -7.3614 … ]
                   OwnSequence: {1×16 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10 10 10 10 10 10 10 10 10 10 10 11 11 10 9]
            MeanSequenceLength: 10.0625
               DeficitEditData: [8285×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

16 sequences from 3D structures
Using 8285 random sequences, 0 from an alignment, and 16 from 3D structures
Group 155, IL_38507.2  has acceptance rules AlignmentScore >= -25.0903, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.3898
TP   100.00%, TN    96.00%, min    96.00%,  16 3D sequences,     0 alignment sequences, 8266 random sequences,  331 random matches,  9 NTs, cWW-tWH-L-tHS-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 331
1 * Deficit + 3 * Core Edit <= 12.2995
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11
Motif index 12
Motif index 13
Motif index 14
Motif index 15
Motif index 16


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_38634.5'
                     Signature: {'cWW-cWH-L-R-cWW'  ''}
                         NumNT: 8
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 5
                      NumFixed: 16
                      OwnScore: [-7.2389 -7.2389]
                   OwnSequence: {'UGAUC*GCGUA'  'UGAAC*GCGCA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10]
            MeanSequenceLength: 10
               DeficitEditData: [10878×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 10878 random sequences, 0 from an alignment, and 2 from 3D structures
Group 156, IL_38634.5  has acceptance rules AlignmentScore >= -27.2389, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  20.2595
TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 10876 random sequences,  435 random matches,  8 NTs, cWW-cWH-L-R-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 435
1 * Deficit + 3 * Core Edit <= 13.0206
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_38862.4'
                     Signature: {'cWW-cSH-R-tWH-tHS-cWW'  ''}
                         NumNT: 10
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 5
                      Truncate: 6
                      NumFixed: 24
                      OwnScore: [-6.0319 -6.0319 -6.8336 -7.0066 -6.9371]
                   OwnSequence: {'UGUAG*CGAAG'  'UGUAG*CGAAG'  'GGUAG*CAAAC'  'UGUAG*UGAGG'  'CGUAU*AAAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10 10 10 10]
            MeanSequenceLength: 10
               DeficitEditData: [3604×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

5 sequences from 3D structures
Using 3604 random sequences, 0 from an alignment, and 5 from 3D structures
Group 157, IL_38862.4  has acceptance rules AlignmentScore >= -26.0319, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.2276
TP   100.00%, TN    95.99%, min    95.99%,   5 3D sequences,     0 alignment sequences, 3590 random sequences,  144 random matches, 10 NTs, cWW-cSH-R-tWH-tHS-cWW
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 144
1 * Deficit + 3 * Core Edit <= 11.1957
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_38969.1'
                     Signature: {'cWW-L-R-L-cWW-L-L'  ''}
                         NumNT: 9
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 7
                      NumFixed: 32
                      OwnScore: -8.3902
                   OwnSequence: {'CGCUUUUUG*CAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 12
            MeanSequenceLength: 12
               DeficitEditData: [2544×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 2544 random sequences, 0 from an alignment, and 1 from 3D structures
Group 158, IL_38969.1  has acceptance rules AlignmentScore >= -28.3902, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.6603
TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences, 2544 random sequences,  102 random matches,  9 NTs, cWW-L-R-L-cWW-L-L
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 102
1 * Deficit + 3 * Core Edit <= 18.2700
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_41203.4'
                     Signature: {'cWW-L-cWW-L-L-R-cSH'  ''}
                         NumNT: 10
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 11
                      Truncate: 9
                      NumFixed: 32
                      OwnScore: [-6.8048 -6.6751 -6.8963 -6.7204 -6.7204 -6.9423 -6.9320 -7.4948 -8.5333 -8.5333 -7.2838]
                   OwnSequence: {1×11 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10 10 10 10 10 10 10 10 10 10]
            MeanSequenceLength: 10
               DeficitEditData: [6645×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

11 sequences from 3D structures
Using 6645 random sequences, 0 from an alignment, and 11 from 3D structures
Group 159, IL_41203.4  has acceptance rules AlignmentScore >= -26.6751, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  20.5094
TP   100.00%, TN    96.00%, min    96.00%,  11 3D sequences,     0 alignment sequences, 6645 random sequences,  266 random matches, 10 NTs, cWW-L-cWW-L-L-R-cSH
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 266
1 * Deficit + 3 * Core Edit <= 13.8343
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_41344.1'
                     Signature: {'cWW-L-R-L-cWW'  ''}
                         NumNT: 7
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 5
                      NumFixed: 18
                      OwnScore: [-7.0024 -7.3553]
                   OwnSequence: {'GAAG*CAC'  'UCUA*UUAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 8]
            MeanSequenceLength: 7.5000
               DeficitEditData: [11396×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 11396 random sequences, 0 from an alignment, and 2 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 160, IL_41344.1  has acceptance rules AlignmentScore >= -27.0024, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.5024
TP   100.00%, TN    89.87%, min    89.87%,   2 3D sequences,     0 alignment sequences, 11370 random sequences, 1152 random matches,  7 NTs, cWW-L-R-L-cWW
Sensitivity 100.00%, Specificity  89.87%, Minimum  89.87% using method 11
Number of false positives with core edit > 0 is 1152
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_41756.4'
                     Signature: {'cWW-tSH-tHH-cSH-tWH-tHS-cWW-L'  ''}
                         NumNT: 14
                  NumBasepairs: 7
                    Structured: 1
                     NumStacks: 17
                        NumBPh: 4
                         NumBR: 2
                  NumInstances: 4
                      Truncate: 9
                      NumFixed: 30
                      OwnScore: [-6.8896 -6.8896 -6.8896 -7.4789]
                   OwnSequence: {'GGAGUAUG*UGAAAC'  'GGAGUAUG*UGAAAC'  'GGAGUACG*UGAAAC'  'GGAGUACG*UAAAAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [14 14 14 14]
            MeanSequenceLength: 14
               DeficitEditData: [1225×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 1225 random sequences, 0 from an alignment, and 4 from 3D structures
Decreased cutoff from  20.9400 because the cutoff seemed overly generous
Group 161, IL_41756.4  has acceptance rules AlignmentScore >= -26.8896, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.8896
TP   100.00%, TN    97.55%, min    97.55%,   4 3D sequences,     0 alignment sequences, 1225 random sequences,   30 random matches, 14 NTs, cWW-tSH-tHH-cSH-tWH-tHS-cWW-L
Sensitivity 100.00%, Specificity  97.55%, Minimum  97.55% using method 8
Number of false positives with core edit > 0 is 30
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1
Motif index 2
Motif index 3
Motif index 4


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_41853.1'
                     Signature: {'cWW-L-tHH-L-tHS-L-cWW-L-L'  ''}
                         NumNT: 13
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 12
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 10
                      NumFixed: 36
                      OwnScore: -10.1591
                   OwnSequence: {'CAGUGAAAG*CGAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 13
            MeanSequenceLength: 13
               DeficitEditData: [5535×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 5535 random sequences, 0 from an alignment, and 1 from 3D structures
Group 162, IL_41853.1  has acceptance rules AlignmentScore >= -30.1591, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  28.3560
TP   100.00%, TN    96.01%, min    96.01%,   1 3D sequences,     0 alignment sequences, 5535 random sequences,  221 random matches, 13 NTs, cWW-L-tHH-L-tHS-L-cWW-L-L
Sensitivity 100.00%, Specificity  96.01%, Minimum  96.01% using method 6
Number of false positives with core edit > 0 is 221
1 * Deficit + 3 * Core Edit <= 18.1969
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_42032.1'
                     Signature: {'cWW-cSH-cWW-tWH-L-cWW-L-L'  ''}
                         NumNT: 11
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 2
                      Truncate: 8
                      NumFixed: 32
                      OwnScore: [-4.7916 -4.7916]
                   OwnSequence: {'GAGGAAG*CUGC'  'GAGGAAG*CUGC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11]
            MeanSequenceLength: 11
               DeficitEditData: [1838×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 1838 random sequences, 0 from an alignment, and 2 from 3D structures
Group 163, IL_42032.1  has acceptance rules AlignmentScore >= -24.7916, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  23.2027
TP   100.00%, TN    95.97%, min    95.97%,   2 3D sequences,     0 alignment sequences, 1838 random sequences,   74 random matches, 11 NTs, cWW-cSH-cWW-tWH-L-cWW-L-L
Sensitivity 100.00%, Specificity  95.97%, Minimum  95.97% using method 6
Number of false positives with core edit > 0 is 74
1 * Deficit + 3 * Core Edit <= 18.4111
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_42218.2'
                     Signature: {'cWW-L-R-cHW-cWW-L-L-L-R-L'  ''}
                         NumNT: 13
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 4
                         NumBR: 3
                  NumInstances: 5
                      Truncate: 11
                      NumFixed: 38
                      OwnScore: [-8.5114 -8.5114 -8.1750 -9.5840 -9.5840]
                   OwnSequence: {'CGAAAUUCCUUG*CCUG'  'CGAAAUUCCUUG*CCUG'  'CGAAAUUCCUUG*CCCG'  'CCAAAUGCCUCG*CGCG'  'CCAAAUGCCUCG*CGCG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [16 16 16 16 16]
            MeanSequenceLength: 16
               DeficitEditData: [215×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

5 sequences from 3D structures
Using 215 random sequences, 0 from an alignment, and 5 from 3D structures
Decreased cutoff from  23.0944 because the cutoff seemed overly generous
Group 164, IL_42218.2  has acceptance rules AlignmentScore >= -28.1750, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  28.7723
TP   100.00%, TN    98.14%, min    98.14%,   5 3D sequences,     0 alignment sequences,  215 random sequences,    4 random matches, 13 NTs, cWW-L-R-cHW-cWW-L-L-L-R-L
Sensitivity 100.00%, Specificity  98.14%, Minimum  98.14% using method 8
Number of false positives with core edit > 0 is 4
1 * Deficit + 3 * Core Edit <= 20.5974
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_42231.1'
                     Signature: {'cWW-L-R-L-cWW-L-cWW-cSS-L'  ''}
                         NumNT: 12
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 2
                      Truncate: 9
                      NumFixed: 40
                      OwnScore: [-10.7332 -10.7332]
                   OwnSequence: {'UACGAAUAAG*CGCUGGA'  'UACGAAUAAG*CGCUGAA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [17 17]
            MeanSequenceLength: 17
               DeficitEditData: [615×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 615 random sequences, 0 from an alignment, and 2 from 3D structures
Decreased cutoff from  21.8500 because the cutoff seemed overly generous
Group 165, IL_42231.1  has acceptance rules AlignmentScore >= -30.7332, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  31.6401
TP   100.00%, TN    98.05%, min    98.05%,   2 3D sequences,     0 alignment sequences,  615 random sequences,   12 random matches, 12 NTs, cWW-L-R-L-cWW-L-cWW-cSS-L
Sensitivity 100.00%, Specificity  98.05%, Minimum  98.05% using method 8
Number of false positives with core edit > 0 is 12
1 * Deficit + 3 * Core Edit <= 20.9068
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_42314.1'
                     Signature: {'cWW-L-R-L-cWW'  ''}
                         NumNT: 7
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 5
                      NumFixed: 18
                      OwnScore: -5.7576
                   OwnSequence: {'UGUAA*UGA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 8
            MeanSequenceLength: 8
               DeficitEditData: [13602×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 13602 random sequences, 0 from an alignment, and 1 from 3D structures
Group 166, IL_42314.1  has acceptance rules AlignmentScore >= -25.7576, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.6501
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 13587 random sequences,  543 random matches,  7 NTs, cWW-L-R-L-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 543
1 * Deficit + 3 * Core Edit <= 11.8925
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_42626.2'
                     Signature: {'cWW-cWW'  ''}
                         NumNT: 4
                  NumBasepairs: 2
                    Structured: 0
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 14
                      Truncate: 3
                      NumFixed: 12
                      OwnScore: [-6.0047 -4.8482 -8.3033 -4.8482 -8.3803 -4.8482 -5.5430 -5.0163 -5.0163 -6.2754 -6.1984 -5.0137 -5.0137 … ]
                   OwnSequence: {1×14 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 7 6 7 6 6 6 6 6 6 6 6 6]
            MeanSequenceLength: 6.1429
               DeficitEditData: [9156×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

14 sequences from 3D structures
Using 9156 random sequences, 0 from an alignment, and 14 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 167, IL_42626.2  has acceptance rules AlignmentScore >= -24.8482, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  14.3482
TP   100.00%, TN    82.64%, min    82.64%,  14 3D sequences,     0 alignment sequences, 8941 random sequences, 1552 random matches,  4 NTs, cWW-cWW
Sensitivity 100.00%, Specificity  82.64%, Minimum  82.64% using method 11
Number of false positives with core edit > 0 is 1552
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11
Motif index 12
Motif index 13
Motif index 14


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_42771.1'
                     Signature: {'cWW-cWW'  ''}
                         NumNT: 4
                  NumBasepairs: 2
                    Structured: 0
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 6
                      Truncate: 3
                      NumFixed: 12
                      OwnScore: [-4.8145 -4.8145 -4.8145 -4.5634 -4.6999 -4.5079]
                   OwnSequence: {'UUA*UUA'  'UUA*UUA'  'UUA*UUA'  'AAA*UU'  'CAG*CG'  'CAA*UG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 6 5 5 5]
            MeanSequenceLength: 5.5000
               DeficitEditData: [7364×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

6 sequences from 3D structures
Using 7364 random sequences, 0 from an alignment, and 6 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 168, IL_42771.1  has acceptance rules AlignmentScore >= -24.5079, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  14.0079
TP   100.00%, TN    76.59%, min    76.59%,   6 3D sequences,     0 alignment sequences, 7060 random sequences, 1653 random matches,  4 NTs, cWW-cWW
Sensitivity 100.00%, Specificity  76.59%, Minimum  76.59% using method 11
Number of false positives with core edit > 0 is 1653
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_42778.1'
                     Signature: {'cWW-L-R-L-R-L-R-L-cWW'  ''}
                         NumNT: 11
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 7
                      NumFixed: 40
                      OwnScore: -8.7794
                   OwnSequence: {'CAGCAG*CAGCAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 12
            MeanSequenceLength: 12
               DeficitEditData: [6579×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 6579 random sequences, 0 from an alignment, and 1 from 3D structures
Group 169, IL_42778.1  has acceptance rules AlignmentScore >= -28.7794, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.4608
TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences, 6579 random sequences,  264 random matches, 11 NTs, cWW-L-R-L-R-L-R-L-cWW
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 264
1 * Deficit + 3 * Core Edit <= 17.6814
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_42997.3'
                     Signature: {'cWW-L-R-cWW'  ''}
                         NumNT: 6
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 20
                      Truncate: 4
                      NumFixed: 14
                      OwnScore: [-5.1240 -5.7718 -5.5426 -5.1240 -5.1240 -5.5426 -4.4671 -5.1240 -6.5627 -6.5470 -5.0415 -5.0415 -7.6892 … ]
                   OwnSequence: {1×20 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 6 6 6]
            MeanSequenceLength: 6.3500
               DeficitEditData: [7140×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

20 sequences from 3D structures
Using 7140 random sequences, 0 from an alignment, and 20 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 170, IL_42997.3  has acceptance rules AlignmentScore >= -24.4671, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.9671
TP   100.00%, TN    84.48%, min    84.48%,  20 3D sequences,     0 alignment sequences, 6644 random sequences, 1031 random matches,  6 NTs, cWW-L-R-cWW
Sensitivity 100.00%, Specificity  84.48%, Minimum  84.48% using method 11
Number of false positives with core edit > 0 is 1031
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11
Motif index 12
Motif index 13
Motif index 14
Motif index 15
Motif index 16
Motif index 17
Motif index 18
Motif index 19
Motif index 20


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_43140.1'
                     Signature: {'cWW-L-cWW-cWH-L-L'  ''}
                         NumNT: 9
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 8
                      NumFixed: 30
                      OwnScore: -7.2894
                   OwnSequence: {'UGGUUGGGUG*CG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 12
            MeanSequenceLength: 12
               DeficitEditData: [2329×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 2329 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  20.6142 because the cutoff seemed overly generous
Group 171, IL_43140.1  has acceptance rules AlignmentScore >= -27.2894, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  27.2894
TP   100.00%, TN    96.82%, min    96.82%,   1 3D sequences,     0 alignment sequences, 2329 random sequences,   74 random matches,  9 NTs, cWW-L-cWW-cWH-L-L
Sensitivity 100.00%, Specificity  96.82%, Minimum  96.82% using method 8
Number of false positives with core edit > 0 is 74
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_43467.1'
                     Signature: {'cWW-L-R-L-R-L-R-L-R-L-cWW-L-L-R-L'  ''}
                         NumNT: 17
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 14
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 12
                      NumFixed: 58
                      OwnScore: -12.2918
                   OwnSequence: {'AGACGGCACCC*GAAGGCAU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 19
            MeanSequenceLength: 19
               DeficitEditData: [31×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 31 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  22.7469 because the cutoff seemed overly generous
Group 172, IL_43467.1  has acceptance rules AlignmentScore >= -32.2918, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  34.3093
TP   100.00%, TN    96.77%, min    96.77%,   1 3D sequences,     0 alignment sequences,   31 random sequences,    1 random matches, 17 NTs, cWW-L-R-L-R-L-R-L-R-L-cWW-L-L-R-L
Sensitivity 100.00%, Specificity  96.77%, Minimum  96.77% using method 8
Number of false positives with core edit > 0 is 1
1 * Deficit + 3 * Core Edit <= 22.0175
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_43547.1'
                     Signature: {'cWW-tSH-tHH-cSH-tWH-tHS-R-L-cWW-L-cWW'  ''}
                         NumNT: 18
                  NumBasepairs: 8
                    Structured: 1
                     NumStacks: 18
                        NumBPh: 3
                         NumBR: 3
                  NumInstances: 3
                      Truncate: 11
                      NumFixed: 40
                      OwnScore: [-8.2272 -8.2272 -8.4545]
                   OwnSequence: {'CCAGUAGAAC*GAAGAACG'  'CCAGUAGAAC*GAAGAACG'  'UCAGUAGAAC*GAAGAACG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [18 18 18]
            MeanSequenceLength: 18
               DeficitEditData: [84×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 84 random sequences, 0 from an alignment, and 3 from 3D structures
Decreased cutoff from  22.8547 because the cutoff seemed overly generous
Group 173, IL_43547.1  has acceptance rules AlignmentScore >= -28.2272, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  30.1687
TP   100.00%, TN    97.62%, min    97.62%,   3 3D sequences,     0 alignment sequences,   84 random sequences,    2 random matches, 18 NTs, cWW-tSH-tHH-cSH-tWH-tHS-R-L-cWW-L-cWW
Sensitivity 100.00%, Specificity  97.62%, Minimum  97.62% using method 8
Number of false positives with core edit > 0 is 2
1 * Deficit + 3 * Core Edit <= 21.9415
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_43622.1'
                     Signature: {'cWW-cWW-L-cWW-L'  ''}
                         NumNT: 8
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 6
                      NumFixed: 22
                      OwnScore: [-4.3379 -4.3379]
                   OwnSequence: {'UUAAGC*GUA'  'UUAAGC*GUA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9]
            MeanSequenceLength: 9
               DeficitEditData: [12785×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 12785 random sequences, 0 from an alignment, and 2 from 3D structures
Group 174, IL_43622.1  has acceptance rules AlignmentScore >= -24.3379, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  20.1526
TP   100.00%, TN    95.99%, min    95.99%,   2 3D sequences,     0 alignment sequences, 12784 random sequences,  512 random matches,  8 NTs, cWW-cWW-L-cWW-L
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 512
1 * Deficit + 3 * Core Edit <= 15.8148
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_43644.1'
                     Signature: {'cWW-cWW-L-R-cWW'  ''}
                         NumNT: 8
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 5
                      NumFixed: 16
                      OwnScore: [-5.6107 -6.4109]
                   OwnSequence: {'AAUG*CCUU'  'CCCG*CCCG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8]
            MeanSequenceLength: 8
               DeficitEditData: [6147×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 6147 random sequences, 0 from an alignment, and 2 from 3D structures
Group 175, IL_43644.1  has acceptance rules AlignmentScore >= -25.6107, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.7759
TP   100.00%, TN    95.98%, min    95.98%,   2 3D sequences,     0 alignment sequences, 6142 random sequences,  247 random matches,  8 NTs, cWW-cWW-L-R-cWW
Sensitivity 100.00%, Specificity  95.98%, Minimum  95.98% using method 6
Number of false positives with core edit > 0 is 247
1 * Deficit + 3 * Core Edit <= 11.1652
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_43858.1'
                     Signature: {'cWW-tSH-cSH-tWH-cSH-cHW-cWH-cWW-cWW'  ''}
                         NumNT: 15
                  NumBasepairs: 10
                    Structured: 1
                     NumStacks: 17
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 2
                      Truncate: 9
                      NumFixed: 36
                      OwnScore: [-8.3681 -8.0031]
                   OwnSequence: {'UAUUAUAGC*GAAUGUAG'  'UGUUAUAGC*GAAUGUGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [17 17]
            MeanSequenceLength: 17
               DeficitEditData: [79×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 79 random sequences, 0 from an alignment, and 2 from 3D structures
Decreased cutoff from  24.3904 because the cutoff seemed overly generous
Group 176, IL_43858.1  has acceptance rules AlignmentScore >= -28.0031, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  31.6928
TP   100.00%, TN    97.47%, min    97.47%,   2 3D sequences,     0 alignment sequences,   79 random sequences,    2 random matches, 15 NTs, cWW-tSH-cSH-tWH-cSH-cHW-cWH-cWW-cWW
Sensitivity 100.00%, Specificity  97.47%, Minimum  97.47% using method 8
Number of false positives with core edit > 0 is 2
1 * Deficit + 3 * Core Edit <= 23.6897
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_44325.1'
                     Signature: {'cWW-cWH-cWW-L'  ''}
                         NumNT: 6
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 5
                      NumFixed: 22
                      OwnScore: -5.8210
                   OwnSequence: {'GCUAG*CAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 8
            MeanSequenceLength: 8
               DeficitEditData: [14698×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 14698 random sequences, 0 from an alignment, and 1 from 3D structures
Group 177, IL_44325.1  has acceptance rules AlignmentScore >= -25.8210, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.9104
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 14695 random sequences,  588 random matches,  6 NTs, cWW-cWH-cWW-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 588
1 * Deficit + 3 * Core Edit <= 11.0894
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_44438.1'
                     Signature: {'cWW-L-R-L-R-L-R-L-R-cWW'  ''}
                         NumNT: 12
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 7
                      NumFixed: 44
                      OwnScore: -7.9246
                   OwnSequence: {'UGAUCU*AGCGUA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 12
            MeanSequenceLength: 12
               DeficitEditData: [6243×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 6243 random sequences, 0 from an alignment, and 1 from 3D structures
Group 178, IL_44438.1  has acceptance rules AlignmentScore >= -27.9246, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.0955
TP   100.00%, TN    95.74%, min    95.74%,   1 3D sequences,     0 alignment sequences, 6242 random sequences,  266 random matches, 12 NTs, cWW-L-R-L-R-L-R-L-R-cWW
Sensitivity 100.00%, Specificity  95.74%, Minimum  95.74% using method 6
Number of false positives with core edit > 0 is 266
1 * Deficit + 3 * Core Edit <= 18.1709
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_44465.1'
                     Signature: {'cWW-L-R-cWW'  ''}
                         NumNT: 6
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 9
                      Truncate: 4
                      NumFixed: 20
                      OwnScore: [-3.9728 -3.9728 -4.2593 -4.1976 -4.5256 -5.0594 -4.5256 -7.3112 -7.9510]
                   OwnSequence: {'UGA*UGA'  'UGA*UGA'  'CGG*CGG'  'UGU*AGA'  'UGG*UGA'  'CAA*UGG'  'UGG*UGA'  'GUA*UUC'  'GGAG*CGC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 6 6 6 6 6 6 7]
            MeanSequenceLength: 6.1111
               DeficitEditData: [8517×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

9 sequences from 3D structures
Using 8517 random sequences, 0 from an alignment, and 9 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 179, IL_44465.1  has acceptance rules AlignmentScore >= -23.9728, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.4728
TP   100.00%, TN    83.00%, min    83.00%,   9 3D sequences,     0 alignment sequences, 8111 random sequences, 1379 random matches,  6 NTs, cWW-L-R-cWW
Sensitivity 100.00%, Specificity  83.00%, Minimum  83.00% using method 11
Number of false positives with core edit > 0 is 1379
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_44624.1'
                     Signature: {'cWW-tWH-cWW-L-cWW-tSS-cSS-cWW-L'  ''}
                         NumNT: 14
                  NumBasepairs: 7
                    Structured: 1
                     NumStacks: 12
                        NumBPh: 1
                         NumBR: 2
                  NumInstances: 2
                      Truncate: 11
                      NumFixed: 32
                      OwnScore: [-8.0579 -8.0579]
                   OwnSequence: {'CUGAGAAAUAC*GGUG'  'CUGAGAAAUAC*GGUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [15 15]
            MeanSequenceLength: 15
               DeficitEditData: [583×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 583 random sequences, 0 from an alignment, and 2 from 3D structures
Decreased cutoff from  21.1183 because the cutoff seemed overly generous
Group 180, IL_44624.1  has acceptance rules AlignmentScore >= -28.0579, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  28.0579
TP   100.00%, TN    97.60%, min    97.60%,   2 3D sequences,     0 alignment sequences,  583 random sequences,   14 random matches, 14 NTs, cWW-tWH-cWW-L-cWW-tSS-cSS-cWW-L
Sensitivity 100.00%, Specificity  97.60%, Minimum  97.60% using method 8
Number of false positives with core edit > 0 is 14
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_44874.1'
                     Signature: {'cWW-tSH-tHW-L-cWW-L-L'  ''}
                         NumNT: 11
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 2
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 8
                      NumFixed: 28
                      OwnScore: -6.4783
                   OwnSequence: {'CGAACCC*GUAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 11
            MeanSequenceLength: 11
               DeficitEditData: [7265×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 7265 random sequences, 0 from an alignment, and 1 from 3D structures
Group 181, IL_44874.1  has acceptance rules AlignmentScore >= -26.4783, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.4306
TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences, 7265 random sequences,  291 random matches, 11 NTs, cWW-tSH-tHW-L-cWW-L-L
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 291
1 * Deficit + 3 * Core Edit <= 18.9524
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_45444.1'
                     Signature: {'cWW-L-R-L-R-L-cWW'  ''}
                         NumNT: 9
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 6
                      NumFixed: 26
                      OwnScore: [-5.2814 -5.2814]
                   OwnSequence: {'CCGAGC*GGAG'  'CCGAGC*GGAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10]
            MeanSequenceLength: 10
               DeficitEditData: [12281×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 12281 random sequences, 0 from an alignment, and 2 from 3D structures
Group 182, IL_45444.1  has acceptance rules AlignmentScore >= -25.2814, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  22.4274
TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 12281 random sequences,  491 random matches,  9 NTs, cWW-L-R-L-R-L-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 491
1 * Deficit + 3 * Core Edit <= 17.1460
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_45896.1'
                     Signature: {'cWW-cWW-cWW'  ''}
                         NumNT: 11
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 8
                      NumFixed: 40
                      OwnScore: -18.9206
                   OwnSequence: {'CAGUAAUAUG*CUUACAAAAUGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 22
            MeanSequenceLength: 22
               DeficitEditData: [8×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 8 random sequences, 0 from an alignment, and 1 from 3D structures
Group 183, IL_45896.1  has acceptance rules AlignmentScore >= -38.9206, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  39.7206
TP   100.00%, TN    87.50%, min    87.50%,   1 3D sequences,     0 alignment sequences,    8 random sequences,    1 random matches, 11 NTs, cWW-cWW-cWW
Sensitivity 100.00%, Specificity  87.50%, Minimum  87.50% using method 1
Number of false positives with core edit > 0 is 1
1 * Deficit + 3 * Core Edit <= 20.8000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_46086.1'
                     Signature: {'cWW-L-cWW-L-L-R'  ''}
                         NumNT: 8
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 7
                      NumFixed: 28
                      OwnScore: -5.7785
                   OwnSequence: {'CAACAAG*UG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 9
            MeanSequenceLength: 9
               DeficitEditData: [11841×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 11841 random sequences, 0 from an alignment, and 1 from 3D structures
Group 184, IL_46086.1  has acceptance rules AlignmentScore >= -25.7785, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  19.9517
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 11839 random sequences,  474 random matches,  8 NTs, cWW-L-cWW-L-L-R
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 474
1 * Deficit + 3 * Core Edit <= 14.1733
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_46112.1'
                     Signature: {'cWW-L-cWW-L-L-R-L'  ''}
                         NumNT: 9
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 8
                      NumFixed: 32
                      OwnScore: -8.6535
                   OwnSequence: {'AACAUUUUC*GU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 11
            MeanSequenceLength: 11
               DeficitEditData: [4984×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 4984 random sequences, 0 from an alignment, and 1 from 3D structures
Group 185, IL_46112.1  has acceptance rules AlignmentScore >= -28.6535, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.1449
TP   100.00%, TN    95.89%, min    95.89%,   1 3D sequences,     0 alignment sequences, 4984 random sequences,  205 random matches,  9 NTs, cWW-L-cWW-L-L-R-L
Sensitivity 100.00%, Specificity  95.89%, Minimum  95.89% using method 6
Number of false positives with core edit > 0 is 205
1 * Deficit + 3 * Core Edit <= 16.4913
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_46174.3'
                     Signature: {'cWW-cSS-tSS-tSH-L-cWW-tHW-cWW'  ''}
                         NumNT: 12
                  NumBasepairs: 7
                    Structured: 1
                     NumStacks: 13
                        NumBPh: 2
                         NumBR: 4
                  NumInstances: 5
                      Truncate: 8
                      NumFixed: 32
                      OwnScore: [-8.8745 -8.8745 -10.2088 -8.7917 -13.8986]
                   OwnSequence: {'UUUCAACG*UAUCAA'  'UUUCAACG*UAUCAA'  'CGACGAUC*GAUUAG'  'CGACGACG*CAUCAG'  'CAAUGACG*UAAGACAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [14 14 14 14 16]
            MeanSequenceLength: 14.4000
               DeficitEditData: [1588×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

5 sequences from 3D structures
Using 1588 random sequences, 0 from an alignment, and 5 from 3D structures
Decreased cutoff from  20.6110 because the cutoff seemed overly generous
Group 186, IL_46174.3  has acceptance rules AlignmentScore >= -28.7917, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  28.7917
TP   100.00%, TN    96.66%, min    96.66%,   5 3D sequences,     0 alignment sequences, 1588 random sequences,   53 random matches, 12 NTs, cWW-cSS-tSS-tSH-L-cWW-tHW-cWW
Sensitivity 100.00%, Specificity  96.66%, Minimum  96.66% using method 8
Number of false positives with core edit > 0 is 53
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_46387.1'
                     Signature: {'cWW-cWW-L-cWW-L'  ''}
                         NumNT: 8
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 3
                      Truncate: 6
                      NumFixed: 22
                      OwnScore: [-6.6113 -6.0473 -7.8356]
                   OwnSequence: {'CCAAU*AUG'  'GUUCU*ACC'  'GGUGG*CGC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8 8]
            MeanSequenceLength: 8
               DeficitEditData: [12152×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 12152 random sequences, 0 from an alignment, and 3 from 3D structures
Group 187, IL_46387.1  has acceptance rules AlignmentScore >= -26.0473, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.7140
TP   100.00%, TN    96.00%, min    96.00%,   3 3D sequences,     0 alignment sequences, 12147 random sequences,  486 random matches,  8 NTs, cWW-cWW-L-cWW-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 486
1 * Deficit + 3 * Core Edit <= 9.6667
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_47074.2'
                     Signature: {'cWW-L-cWW-L'  ''}
                         NumNT: 6
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 4
                      Truncate: 5
                      NumFixed: 20
                      OwnScore: [-3.3677 -3.3677 -5.3934 -7.3315]
                   OwnSequence: {'UAGU*AG'  'UAGU*AG'  'AAGC*GU'  'UUUCGA*UG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 6 8]
            MeanSequenceLength: 6.5000
               DeficitEditData: [10459×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 10459 random sequences, 0 from an alignment, and 4 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 188, IL_47074.2  has acceptance rules AlignmentScore >= -23.3677, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  12.8677
TP   100.00%, TN    94.75%, min    94.75%,   4 3D sequences,     0 alignment sequences, 10391 random sequences,  546 random matches,  6 NTs, cWW-L-cWW-L
Sensitivity 100.00%, Specificity  94.75%, Minimum  94.75% using method 11
Number of false positives with core edit > 0 is 546
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_47078.3'
                     Signature: {'cWW-cWS-L-cWW-L'  ''}
                         NumNT: 7
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 4
                      Truncate: 6
                      NumFixed: 22
                      OwnScore: [-5.7240 -5.7240 -5.3866 -5.3866]
                   OwnSequence: {'UUCCC*GCA'  'UUCCC*GCA'  'GACAU*AC'  'GACAU*AC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8 7 7]
            MeanSequenceLength: 7.5000
               DeficitEditData: [8450×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 8450 random sequences, 0 from an alignment, and 4 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 189, IL_47078.3  has acceptance rules AlignmentScore >= -25.3866, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  14.8866
TP   100.00%, TN    95.97%, min    95.97%,   4 3D sequences,     0 alignment sequences, 8436 random sequences,  340 random matches,  7 NTs, cWW-cWS-L-cWW-L
Sensitivity 100.00%, Specificity  95.97%, Minimum  95.97% using method 11
Number of false positives with core edit > 0 is 340
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_47087.1'
                     Signature: {'cWW-L-cWW-L-cWW-tWH-L-L'  ''}
                         NumNT: 11
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 9
                      NumFixed: 36
                      OwnScore: -6.0951
                   OwnSequence: {'GGAACUAC*GCC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 11
            MeanSequenceLength: 11
               DeficitEditData: [5905×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 5905 random sequences, 0 from an alignment, and 1 from 3D structures
Group 190, IL_47087.1  has acceptance rules AlignmentScore >= -26.0951, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.8540
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 5905 random sequences,  236 random matches, 11 NTs, cWW-L-cWW-L-cWW-tWH-L-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 236
1 * Deficit + 3 * Core Edit <= 18.7590
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_47108.1'
                     Signature: {'cWW-L-R-L-tHH-L-cWW'  ''}
                         NumNT: 9
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 7
                      NumFixed: 26
                      OwnScore: -6.2610
                   OwnSequence: {'UGAAAG*UUAA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 10
            MeanSequenceLength: 10
               DeficitEditData: [13193×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 13193 random sequences, 0 from an alignment, and 1 from 3D structures
Group 191, IL_47108.1  has acceptance rules AlignmentScore >= -26.2610, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  22.4419
TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences, 13189 random sequences,  529 random matches,  9 NTs, cWW-L-R-L-tHH-L-cWW
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 529
1 * Deficit + 3 * Core Edit <= 16.1809
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_47346.2'
                     Signature: {'cWW-tSH-L-R-tHH-tHS-cWW'  ''}
                         NumNT: 12
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 14
                        NumBPh: 5
                         NumBR: 2
                  NumInstances: 7
                      Truncate: 7
                      NumFixed: 20
                      OwnScore: [-6.9211 -6.9211 -6.5492 -6.1326 -6.6110 -6.1326 -6.1326]
                   OwnSequence: {1×7 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [13 13 13 13 13 13 13]
            MeanSequenceLength: 13
               DeficitEditData: [2771×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

7 sequences from 3D structures
Using 2771 random sequences, 0 from an alignment, and 7 from 3D structures
Group 192, IL_47346.2  has acceptance rules AlignmentScore >= -26.1326, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.4664
TP   100.00%, TN    95.99%, min    95.99%,   7 3D sequences,     0 alignment sequences, 2771 random sequences,  111 random matches, 12 NTs, cWW-tSH-L-R-tHH-tHS-cWW
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 111
1 * Deficit + 3 * Core Edit <= 18.3337
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_47972.1'
                     Signature: {'cWW-L-R-L-cWW-L'  ''}
                         NumNT: 8
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 6
                      NumFixed: 28
                      OwnScore: -5.3631
                   OwnSequence: {'CGAUG*CAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 8
            MeanSequenceLength: 8
               DeficitEditData: [14493×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 14493 random sequences, 0 from an alignment, and 1 from 3D structures
Group 193, IL_47972.1  has acceptance rules AlignmentScore >= -25.3631, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.3542
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 14489 random sequences,  580 random matches,  8 NTs, cWW-L-R-L-cWW-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 580
1 * Deficit + 3 * Core Edit <= 11.9911
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_48076.6'
                     Signature: {'cWW-cSH-cWW'  ''}
                         NumNT: 5
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 41
                      Truncate: 4
                      NumFixed: 20
                      OwnScore: [-3.3226 -3.3226 -3.8533 -3.3226 -3.3226 -5.2846 -4.5287 -3.6770 -4.0575 -4.0575 -4.1294 -4.1765 -4.7540 … ]
                   OwnSequence: {1×41 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 6 5 5 5 6 5 5 6]
            MeanSequenceLength: 5.0732
               DeficitEditData: [7297×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

41 sequences from 3D structures
Using 7297 random sequences, 0 from an alignment, and 41 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 194, IL_48076.6  has acceptance rules AlignmentScore >= -23.3226, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  12.8226
TP   100.00%, TN    92.71%, min    92.71%,  41 3D sequences,     0 alignment sequences, 6156 random sequences,  449 random matches,  5 NTs, cWW-cSH-cWW
Sensitivity 100.00%, Specificity  92.71%, Minimum  92.71% using method 11
Number of false positives with core edit > 0 is 449
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11
Motif index 12
Motif index 13
Motif index 14
Motif index 15
Motif index 16
Motif index 17
Motif index 18
Motif index 19
Motif index 20
Motif index 21
Motif index 22
Motif index 23
Motif index 24
Motif index 25
Motif index 26
Motif index 27
Motif index 28
Motif index 29
Motif index 30
Motif index 31
Motif index 32
Motif index 33
Motif index 34
Motif index 35
Motif index 36
Motif index 37
Motif index 38
Motif index 39
Motif index 40
Motif index 41


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_48444.6'
                     Signature: {'cWW-L-R-cWW-cWW'  ''}
                         NumNT: 8
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 4
                      Truncate: 5
                      NumFixed: 22
                      OwnScore: [-7.8168 -7.8168 -11.8582 -9.8020]
                   OwnSequence: {'UAAG*CAGUA'  'UAAG*CAGUA'  'CUAC*GGUCAG'  'CGAU*AGAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 10 9]
            MeanSequenceLength: 9.2500
               DeficitEditData: [18646×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 18646 random sequences, 0 from an alignment, and 4 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 195, IL_48444.6  has acceptance rules AlignmentScore >= -27.8168, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.3168
TP   100.00%, TN    95.80%, min    95.80%,   4 3D sequences,     0 alignment sequences, 18636 random sequences,  782 random matches,  8 NTs, cWW-L-R-cWW-cWW
Sensitivity 100.00%, Specificity  95.80%, Minimum  95.80% using method 11
Number of false positives with core edit > 0 is 782
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_49061.1'
                     Signature: {'cWW-L-R-L-cWW-L'  ''}
                         NumNT: 8
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 6
                      Truncate: 6
                      NumFixed: 22
                      OwnScore: [-8.6778 -8.8115 -7.2469 -7.6615 -8.3503 -14.3321]
                   OwnSequence: {'CGGGAG*CAG'  'CGGAAA*UGG'  'CCGAG*CAG'  'GGAAG*CAC'  'GGAUC*GAC'  'UCUGUGA*UGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 8 8 8 10]
            MeanSequenceLength: 8.6667
               DeficitEditData: [18294×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

6 sequences from 3D structures
Using 18294 random sequences, 0 from an alignment, and 6 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 196, IL_49061.1  has acceptance rules AlignmentScore >= -27.2469, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.7469
TP   100.00%, TN    95.69%, min    95.69%,   6 3D sequences,     0 alignment sequences, 18267 random sequences,  788 random matches,  8 NTs, cWW-L-R-L-cWW-L
Sensitivity 100.00%, Specificity  95.69%, Minimum  95.69% using method 11
Number of false positives with core edit > 0 is 788
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_49612.1'
                     Signature: {'cWW-L-R-L-R-L-cWW-L'  ''}
                         NumNT: 10
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 7
                      NumFixed: 30
                      OwnScore: [-10.7763 -10.8661]
                   OwnSequence: {'CGGCAU*AUGG'  'GUCUGUGA*UGGC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 12]
            MeanSequenceLength: 11
               DeficitEditData: [18715×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 18715 random sequences, 0 from an alignment, and 2 from 3D structures
Group 197, IL_49612.1  has acceptance rules AlignmentScore >= -30.7763, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.3442
TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 18715 random sequences,  749 random matches, 10 NTs, cWW-L-R-L-R-L-cWW-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 749
1 * Deficit + 3 * Core Edit <= 14.5679
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_49714.1'
                     Signature: {'cWW-L-cWW-L-L'  ''}
                         NumNT: 7
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 6
                      NumFixed: 24
                      OwnScore: -4.5706
                   OwnSequence: {'GAACUAC*GC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 9
            MeanSequenceLength: 9
               DeficitEditData: [7570×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 7570 random sequences, 0 from an alignment, and 1 from 3D structures
Group 198, IL_49714.1  has acceptance rules AlignmentScore >= -24.5706, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.7941
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 7568 random sequences,  303 random matches,  7 NTs, cWW-L-cWW-L-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 303
1 * Deficit + 3 * Core Edit <= 13.2236
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_49751.4'
                     Signature: {'cWW-cWW-cWW-cWW-cWW'  ''}
                         NumNT: 10
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 12
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 16
                      Truncate: 6
                      NumFixed: 18
                      OwnScore: [-8.1049 -8.1049 -7.3230 -7.2614 -7.2614 -7.3230 -8.7767 -8.9331 -10.7372 -10.6441 -12.2580 -10.6962 … ]
                   OwnSequence: {1×16 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 11]
            MeanSequenceLength: 10.0625
               DeficitEditData: [6492×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

16 sequences from 3D structures
Using 6492 random sequences, 0 from an alignment, and 16 from 3D structures
Group 199, IL_49751.4  has acceptance rules AlignmentScore >= -27.2614, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  18.5570
TP   100.00%, TN    96.01%, min    96.01%,  16 3D sequences,     0 alignment sequences, 6486 random sequences,  259 random matches, 10 NTs, cWW-cWW-cWW-cWW-cWW
Sensitivity 100.00%, Specificity  96.01%, Minimum  96.01% using method 6
Number of false positives with core edit > 0 is 259
1 * Deficit + 3 * Core Edit <= 11.2956
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11
Motif index 12
Motif index 13
Motif index 14
Motif index 15
Motif index 16


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_49767.8'
                     Signature: {'cWW-cWW-tWH-L-tHS-cWW'  ''}
                         NumNT: 11
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 6
                      Truncate: 7
                      NumFixed: 22
                      OwnScore: [-6.7495 -6.7495 -6.8423 -7.5303 -7.5054 -10.5700]
                   OwnSequence: {'GAUAAC*GGAAGC'  'GAUAAC*GGAAGC'  'GGUAAG*CGAAAC'  'GAUAAG*UGAAGC'  'GAUAAG*CGAAAC'  'UCUAAA*UGAUGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [12 12 12 12 12 12]
            MeanSequenceLength: 12
               DeficitEditData: [5548×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

6 sequences from 3D structures
Using 5548 random sequences, 0 from an alignment, and 6 from 3D structures
Group 200, IL_49767.8  has acceptance rules AlignmentScore >= -26.7495, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  22.5979
TP   100.00%, TN    96.00%, min    96.00%,   6 3D sequences,     0 alignment sequences, 5547 random sequences,  222 random matches, 11 NTs, cWW-cWW-tWH-L-tHS-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 222
1 * Deficit + 3 * Core Edit <= 15.8484
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_49867.1'
                     Signature: {'cWW-cWW-L-R-L-R-tHW-R-L-L-cWW'  ''}
                         NumNT: 15
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 13
                        NumBPh: 3
                         NumBR: 2
                  NumInstances: 1
                      Truncate: 9
                      NumFixed: 32
                      OwnScore: -7.3205
                   OwnSequence: {'CAAUACUC*GUGCCGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 15
            MeanSequenceLength: 15
               DeficitEditData: [294×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 294 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  24.3960 because the cutoff seemed overly generous
Group 201, IL_49867.1  has acceptance rules AlignmentScore >= -27.3205, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  30.9335
TP   100.00%, TN    97.96%, min    97.96%,   1 3D sequences,     0 alignment sequences,  294 random sequences,    6 random matches, 15 NTs, cWW-cWW-L-R-L-R-tHW-R-L-L-cWW
Sensitivity 100.00%, Specificity  97.96%, Minimum  97.96% using method 8
Number of false positives with core edit > 0 is 6
1 * Deficit + 3 * Core Edit <= 23.6130
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_49971.1'
                     Signature: {'cWW-cWH-cWW-cWW-L-L-R'  ''}
                         NumNT: 10
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 0
                         NumBR: 3
                  NumInstances: 1
                      Truncate: 8
                      NumFixed: 28
                      OwnScore: -5.8516
                   OwnSequence: {'CGCAUUUGG*CGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 12
            MeanSequenceLength: 12
               DeficitEditData: [1929×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 1929 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  20.1923 because the cutoff seemed overly generous
Group 202, IL_49971.1  has acceptance rules AlignmentScore >= -25.8516, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.8516
TP   100.00%, TN    96.06%, min    96.06%,   1 3D sequences,     0 alignment sequences, 1929 random sequences,   76 random matches, 10 NTs, cWW-cWH-cWW-cWW-L-L-R
Sensitivity 100.00%, Specificity  96.06%, Minimum  96.06% using method 8
Number of false positives with core edit > 0 is 76
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_50694.7'
                     Signature: {'cWW-tSH-cWW-L'  ''}
                         NumNT: 6
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 27
                      Truncate: 5
                      NumFixed: 20
                      OwnScore: [-3.6490 -3.6490 -3.6490 -3.6490 -3.6490 -4.0897 -3.4958 -4.0897 -5.4704 -3.5673 -3.5673 -4.3093 -4.0897 … ]
                   OwnSequence: {1×27 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6]
            MeanSequenceLength: 6
               DeficitEditData: [5676×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

27 sequences from 3D structures
Using 5676 random sequences, 0 from an alignment, and 27 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 203, IL_50694.7  has acceptance rules AlignmentScore >= -23.4958, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  12.9958
TP   100.00%, TN    91.66%, min    91.66%,  27 3D sequences,     0 alignment sequences, 5347 random sequences,  446 random matches,  6 NTs, cWW-tSH-cWW-L
Sensitivity 100.00%, Specificity  91.66%, Minimum  91.66% using method 11
Number of false positives with core edit > 0 is 446
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11
Motif index 12
Motif index 13
Motif index 14
Motif index 15
Motif index 16
Motif index 17
Motif index 18
Motif index 19
Motif index 20
Motif index 21
Motif index 22
Motif index 23
Motif index 24
Motif index 25
Motif index 26
Motif index 27


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_50715.3'
                     Signature: {'cWW-tSH-tHH-L-R-L-R-L-tWW-L-cWW-L-L-L-R-L'  ''}
                         NumNT: 21
                  NumBasepairs: 7
                    Structured: 1
                     NumStacks: 19
                        NumBPh: 4
                         NumBR: 1
                  NumInstances: 4
                      Truncate: 15
                      NumFixed: 52
                      OwnScore: [-16.8843 -17.8317 -15.7279 -14.8806]
                   OwnSequence: {1×4 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [24 24 23 23]
            MeanSequenceLength: 23.5000
               DeficitEditData: [19.3879 5]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 1 random sequences, 0 from an alignment, and 4 from 3D structures
Group 204, IL_50715.3  has acceptance rules AlignmentScore >= -34.8806, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  39.8806
TP   100.00%, TN   100.00%, min   100.00%,   4 3D sequences,     0 alignment sequences,    1 random sequences,    0 random matches, 21 NTs, cWW-tSH-tHH-L-R-L-R-L-tWW-L-cWW-L-L-L-R-L
Sensitivity 100.00%, Specificity 100.00%, Minimum 100.00% using method 1
Number of false positives with core edit > 0 is 0
1 * Deficit + 3 * Core Edit <= 25.0000
Motif index 1
Motif index 2
Motif index 3
Motif index 4


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_50730.2'
                     Signature: {'cWW-tSH-tHS-tHS-cWW'  ''}
                         NumNT: 10
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 11
                        NumBPh: 2
                         NumBR: 2
                  NumInstances: 19
                      Truncate: 6
                      NumFixed: 18
                      OwnScore: [-6.6772 -6.6772 -8.6957 -6.3745 -6.3745 -6.4891 -6.3745 -6.3745 -8.7065 -6.4385 -7.3632 -8.7065 -6.3745 … ]
                   OwnSequence: {1×19 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10]
            MeanSequenceLength: 10
               DeficitEditData: [4907×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

19 sequences from 3D structures
Using 4907 random sequences, 0 from an alignment, and 19 from 3D structures
Group 205, IL_50730.2  has acceptance rules AlignmentScore >= -26.3745, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.9585
TP   100.00%, TN    96.00%, min    96.00%,  19 3D sequences,     0 alignment sequences, 4898 random sequences,  196 random matches, 10 NTs, cWW-tSH-tHS-tHS-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 196
1 * Deficit + 3 * Core Edit <= 10.5840
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11
Motif index 12
Motif index 13
Motif index 14
Motif index 15
Motif index 16
Motif index 17
Motif index 18
Motif index 19


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_51191.1'
                     Signature: {'cWW-L-R-L-cWW-L-L'  ''}
                         NumNT: 9
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 7
                      NumFixed: 32
                      OwnScore: -6.9316
                   OwnSequence: {'CAGGUGU*AAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 10
            MeanSequenceLength: 10
               DeficitEditData: [15111×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 15111 random sequences, 0 from an alignment, and 1 from 3D structures
Group 206, IL_51191.1  has acceptance rules AlignmentScore >= -26.9316, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.0278
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 15111 random sequences,  604 random matches,  9 NTs, cWW-L-R-L-cWW-L-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 604
1 * Deficit + 3 * Core Edit <= 17.0962
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_51265.3'
                     Signature: {'cWW-tSS-tHS-tSH-cWW-L'  ''}
                         NumNT: 10
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 0
                         NumBR: 6
                  NumInstances: 6
                      Truncate: 7
                      NumFixed: 26
                      OwnScore: [-4.5912 -4.5912 -4.5912 -5.6956 -4.8730 -4.8730]
                   OwnSequence: {'CAAUGAG*UGAG'  'CAAUGAG*UGAG'  'CAAUGAG*UGAG'  'CGAUGAG*CGAG'  'CAAUGAG*CGAG'  'CAAUGAG*CGAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11 11 11 11 11]
            MeanSequenceLength: 11
               DeficitEditData: [3259×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

6 sequences from 3D structures
Using 3259 random sequences, 0 from an alignment, and 6 from 3D structures
Group 207, IL_51265.3  has acceptance rules AlignmentScore >= -24.5912, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  20.3618
TP   100.00%, TN    96.01%, min    96.01%,   6 3D sequences,     0 alignment sequences, 3258 random sequences,  130 random matches, 10 NTs, cWW-tSS-tHS-tSH-cWW-L
Sensitivity 100.00%, Specificity  96.01%, Minimum  96.01% using method 6
Number of false positives with core edit > 0 is 130
1 * Deficit + 3 * Core Edit <= 15.7706
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_51387.2'
                     Signature: {'cWW-cSH-cWW-cWW'  ''}
                         NumNT: 7
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 20
                      Truncate: 5
                      NumFixed: 22
                      OwnScore: [-4.9486 -4.9623 -4.9486 -4.9623 -5.3277 -6.7656 -6.7656 -6.3665 -6.3665 -8.4809 -8.4809 -6.3665 -8.1753 … ]
                   OwnSequence: {1×20 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 7 7 7 7 8 8 8 8 8 8 8 8 8 8 8 8 8 7 7]
            MeanSequenceLength: 7.6500
               DeficitEditData: [9782×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

20 sequences from 3D structures
Using 9782 random sequences, 0 from an alignment, and 20 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 208, IL_51387.2  has acceptance rules AlignmentScore >= -24.9486, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  14.4486
TP   100.00%, TN    95.14%, min    95.14%,  20 3D sequences,     0 alignment sequences, 9711 random sequences,  472 random matches,  7 NTs, cWW-cSH-cWW-cWW
Sensitivity 100.00%, Specificity  95.14%, Minimum  95.14% using method 11
Number of false positives with core edit > 0 is 472
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11
Motif index 12
Motif index 13
Motif index 14
Motif index 15
Motif index 16
Motif index 17
Motif index 18
Motif index 19
Motif index 20


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_51454.3'
                     Signature: {'cWW-cSH-cWW'  ''}
                         NumNT: 5
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 45
                      Truncate: 4
                      NumFixed: 22
                      OwnScore: [-3.9595 -5.0790 -3.9595 -3.9595 -5.0790 -8.3891 -2.7505 -4.4829 -2.7505 -2.7505 -3.9595 -2.7505 -2.7505 … ]
                   OwnSequence: {1×45 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [5 5 5 5 5 6 5 5 5 5 5 5 5 5 5 5 5 5 5 5 6 5 5 5 5 5 5 6 5 5 6 6 5 5 6 5 5 6 6 5 5 5 5 5 5]
            MeanSequenceLength: 5.1778
               DeficitEditData: [6497×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

45 sequences from 3D structures
Using 6497 random sequences, 0 from an alignment, and 45 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 209, IL_51454.3  has acceptance rules AlignmentScore >= -22.7382, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  12.2382
TP   100.00%, TN    95.08%, min    95.08%,  45 3D sequences,     0 alignment sequences, 5792 random sequences,  285 random matches,  5 NTs, cWW-cSH-cWW
Sensitivity 100.00%, Specificity  95.08%, Minimum  95.08% using method 11
Number of false positives with core edit > 0 is 285
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11
Motif index 12
Motif index 13
Motif index 14
Motif index 15
Motif index 16
Motif index 17
Motif index 18
Motif index 19
Motif index 20
Motif index 21
Motif index 22
Motif index 23
Motif index 24
Motif index 25
Motif index 26
Motif index 27
Motif index 28
Motif index 29
Motif index 30
Motif index 31
Motif index 32
Motif index 33
Motif index 34
Motif index 35
Motif index 36
Motif index 37
Motif index 38
Motif index 39
Motif index 40
Motif index 41
Motif index 42
Motif index 43
Motif index 44
Motif index 45


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_51479.1'
                     Signature: {'cWW-L-R-L-cWW'  ''}
                         NumNT: 7
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 10
                      Truncate: 5
                      NumFixed: 18
                      OwnScore: [-6.9950 -6.9950 -6.9950 -6.9950 -8.3757 -8.5467 -10.2887 -9.6056 -8.5467 -10.0943]
                   OwnSequence: {1×10 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 9 9 9 8 8 8 8 8]
            MeanSequenceLength: 8.5000
               DeficitEditData: [12157×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

10 sequences from 3D structures
Using 12157 random sequences, 0 from an alignment, and 10 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 210, IL_51479.1  has acceptance rules AlignmentScore >= -26.9950, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.4950
TP   100.00%, TN    93.24%, min    93.24%,  10 3D sequences,     0 alignment sequences, 12127 random sequences,  820 random matches,  7 NTs, cWW-L-R-L-cWW
Sensitivity 100.00%, Specificity  93.24%, Minimum  93.24% using method 11
Number of false positives with core edit > 0 is 820
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_52743.1'
                     Signature: {'cWW-tSW-L-cSW-L-cWW-L'  ''}
                         NumNT: 10
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 2
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 8
                      NumFixed: 34
                      OwnScore: -3.9423
                   OwnSequence: {'GACAAGA*UAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 10
            MeanSequenceLength: 10
               DeficitEditData: [3874×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 3874 random sequences, 0 from an alignment, and 1 from 3D structures
Group 211, IL_52743.1  has acceptance rules AlignmentScore >= -23.9423, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  21.7916
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 3874 random sequences,  155 random matches, 10 NTs, cWW-tSW-L-cSW-L-cWW-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 155
1 * Deficit + 3 * Core Edit <= 17.8493
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_53448.1'
                     Signature: {'cWW-tWH-cSH-cWW'  ''}
                         NumNT: 8
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 11
                      Truncate: 6
                      NumFixed: 20
                      OwnScore: [-4.0244 -4.0244 -4.0244 -4.0244 -4.0244 -4.0244 -4.0244 -4.0244 -4.0244 -4.3465 -4.0244]
                   OwnSequence: {1×11 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 9 9 9 9 9 9 9 9 9]
            MeanSequenceLength: 9
               DeficitEditData: [5823×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

11 sequences from 3D structures
Using 5823 random sequences, 0 from an alignment, and 11 from 3D structures
Group 212, IL_53448.1  has acceptance rules AlignmentScore >= -24.0244, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  20.5761
TP   100.00%, TN    95.96%, min    95.96%,  11 3D sequences,     0 alignment sequences, 5821 random sequences,  235 random matches,  8 NTs, cWW-tWH-cSH-cWW
Sensitivity 100.00%, Specificity  95.96%, Minimum  95.96% using method 6
Number of false positives with core edit > 0 is 235
1 * Deficit + 3 * Core Edit <= 16.5517
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_53581.1'
                     Signature: {'cWW-tWW-L-tWH-cSS-tSS-tWH-cSS-tWH-R-tSS-R-L-L-cWW-L-cWW'  ''}
                         NumNT: 22
                  NumBasepairs: 12
                    Structured: 1
                     NumStacks: 21
                        NumBPh: 1
                         NumBR: 4
                  NumInstances: 2
                      Truncate: 13
                      NumFixed: 52
                      OwnScore: [-7.6695 -7.6695]
                   OwnSequence: {'GAGAAUGUUAUGG*CAGAGAAAAC'  'GAGAAUGUUAUGG*CAGAGAAAAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [23 23]
            MeanSequenceLength: 23
               DeficitEditData: [0×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 0 random sequences, 0 from an alignment, and 2 from 3D structures
No random sequence matches, so essentially no model-specific cutoff imposed
Decreased cutoff to  25.0000 so that it is possible to reject matches
Group 213, IL_53581.1  has acceptance rules AlignmentScore >= -27.6695, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  32.6695
TP   100.00%, TN      NaN%, min   100.00%,   2 3D sequences,     0 alignment sequences,    0 random sequences,    0 random matches, 22 NTs, cWW-tWW-L-tWH-cSS-tSS-tWH-cSS-tWH-R-tSS-R-L-L-cWW-L-cWW
Sensitivity 100.00%, Specificity    NaN%, Minimum 100.00% using method 12
Number of false positives with core edit > 0 is 0
1 * Deficit + 3 * Core Edit <= 25.0000
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_53596.1'
                     Signature: {'cWW-L-cWW-L-L-R-L'  ''}
                         NumNT: 9
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 8
                      NumFixed: 32
                      OwnScore: [-7.2788 -7.2788]
                   OwnSequence: {'GUGGAACCG*UC'  'GUGGCACCG*UC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11]
            MeanSequenceLength: 11
               DeficitEditData: [6793×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 6793 random sequences, 0 from an alignment, and 2 from 3D structures
Group 214, IL_53596.1  has acceptance rules AlignmentScore >= -27.2788, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.0825
TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 6793 random sequences,  272 random matches,  9 NTs, cWW-L-cWW-L-L-R-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 272
1 * Deficit + 3 * Core Edit <= 17.8037
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_53787.1'
                     Signature: {'cWW-L-cWW-L-L-R-L-R-L-R-L-R'  ''}
                         NumNT: 14
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 13
                      NumFixed: 52
                      OwnScore: -10.4803
                   OwnSequence: {'CUUUCUGCCAAAG*UG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 15
            MeanSequenceLength: 15
               DeficitEditData: [318×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 318 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  20.8723 because the cutoff seemed overly generous
Group 215, IL_53787.1  has acceptance rules AlignmentScore >= -30.4803, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  30.4803
TP   100.00%, TN    97.48%, min    97.48%,   1 3D sequences,     0 alignment sequences,  318 random sequences,    8 random matches, 14 NTs, cWW-L-cWW-L-L-R-L-R-L-R-L-R
Sensitivity 100.00%, Specificity  97.48%, Minimum  97.48% using method 8
Number of false positives with core edit > 0 is 8
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_54041.2'
                     Signature: {'cWW-L-R-L-R-tWH-L-cWW'  ''}
                         NumNT: 11
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 7
                      Truncate: 7
                      NumFixed: 22
                      OwnScore: [-6.0504 -6.0504 -6.0504 -6.0504 -9.6825 -9.6825 -10.6325]
                   OwnSequence: {1×7 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [13 13 13 13 13 13 13]
            MeanSequenceLength: 13
               DeficitEditData: [3438×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

7 sequences from 3D structures
Using 3438 random sequences, 0 from an alignment, and 7 from 3D structures
Decreased cutoff from  20.8983 because the cutoff seemed overly generous
Group 216, IL_54041.2  has acceptance rules AlignmentScore >= -26.0504, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.0504
TP   100.00%, TN    96.80%, min    96.80%,   7 3D sequences,     0 alignment sequences, 3438 random sequences,  110 random matches, 11 NTs, cWW-L-R-L-R-tWH-L-cWW
Sensitivity 100.00%, Specificity  96.80%, Minimum  96.80% using method 8
Number of false positives with core edit > 0 is 110
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_54050.1'
                     Signature: {'cWW-L-R-L-R-L-cWW-L-L'  ''}
                         NumNT: 11
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 2
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 8
                      NumFixed: 34
                      OwnScore: -10.4862
                   OwnSequence: {'UAGUGUCCUUG*CAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 15
            MeanSequenceLength: 15
               DeficitEditData: [381×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 381 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  22.1919 because the cutoff seemed overly generous
Group 217, IL_54050.1  has acceptance rules AlignmentScore >= -30.4862, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  30.4862
TP   100.00%, TN    97.90%, min    97.90%,   1 3D sequences,     0 alignment sequences,  381 random sequences,    8 random matches, 11 NTs, cWW-L-R-L-R-L-cWW-L-L
Sensitivity 100.00%, Specificity  97.90%, Minimum  97.90% using method 8
Number of false positives with core edit > 0 is 8
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_54177.4'
                     Signature: {'cWW-cSW-tWH-L-R-L-R-tHS-cWW'  ''}
                         NumNT: 13
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 11
                        NumBPh: 3
                         NumBR: 4
                  NumInstances: 4
                      Truncate: 8
                      NumFixed: 42
                      OwnScore: [-5.3135 -5.3135 -6.2690 -6.2690]
                   OwnSequence: {'GUGCCAG*CGGUAAUUC'  'GUGCCAG*CGGUAAUUC'  'GUGCCAG*CGGUAAUAC'  'GUGCCAG*CGGUAAUAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [16 16 16 16]
            MeanSequenceLength: 16
               DeficitEditData: [225×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 225 random sequences, 0 from an alignment, and 4 from 3D structures
Decreased cutoff from  25.1534 because the cutoff seemed overly generous
Group 218, IL_54177.4  has acceptance rules AlignmentScore >= -25.3135, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  28.9266
TP   100.00%, TN    97.78%, min    97.78%,   4 3D sequences,     0 alignment sequences,  225 random sequences,    5 random matches, 13 NTs, cWW-cSW-tWH-L-R-L-R-tHS-cWW
Sensitivity 100.00%, Specificity  97.78%, Minimum  97.78% using method 8
Number of false positives with core edit > 0 is 5
1 * Deficit + 3 * Core Edit <= 23.6131
Motif index 1
Motif index 2
Motif index 3
Motif index 4


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_54737.1'
                     Signature: {'cWW-L-R-L-R-L-R-L-R-L-R-L-R-L-R-L-R-L-R'  ''}
                         NumNT: 20
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 15
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 12
                      NumFixed: 58
                      OwnScore: -20.9955
                   OwnSequence: {'CCUUGAUGUGUAGGAUAG*CCUUUAAUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 27
            MeanSequenceLength: 27
               DeficitEditData: [0×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 0 random sequences, 0 from an alignment, and 1 from 3D structures
No random sequence matches, so essentially no model-specific cutoff imposed
Decreased cutoff to  25.0000 so that it is possible to reject matches
Group 219, IL_54737.1  has acceptance rules AlignmentScore >= -40.9955, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  45.9955
TP   100.00%, TN      NaN%, min   100.00%,   1 3D sequences,     0 alignment sequences,    0 random sequences,    0 random matches, 20 NTs, cWW-L-R-L-R-L-R-L-R-L-R-L-R-L-R-L-R-L-R
Sensitivity 100.00%, Specificity    NaN%, Minimum 100.00% using method 12
Number of false positives with core edit > 0 is 0
1 * Deficit + 3 * Core Edit <= 25.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_54896.1'
                     Signature: {'cWW-L-R-L-cWW-L-L-R-L-R'  ''}
                         NumNT: 12
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 10
                      NumFixed: 44
                      OwnScore: -9.0456
                   OwnSequence: {'UGGCGAACAG*CGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 13
            MeanSequenceLength: 13
               DeficitEditData: [4847×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 4847 random sequences, 0 from an alignment, and 1 from 3D structures
Group 220, IL_54896.1  has acceptance rules AlignmentScore >= -29.0456, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  28.0953
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 4847 random sequences,  194 random matches, 12 NTs, cWW-L-R-L-cWW-L-L-R-L-R
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 194
1 * Deficit + 3 * Core Edit <= 19.0497
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_55516.2'
                     Signature: {'cWW-cWW-cSH-cWW'  ''}
                         NumNT: 7
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 7
                      Truncate: 5
                      NumFixed: 22
                      OwnScore: [-6.5277 -6.5551 -6.1092 -5.6175 -5.6175 -9.7277 -8.1729]
                   OwnSequence: {'GAAG*CAC'  'GGGG*UAC'  'GCAC*GAC'  'GCGG*UAC'  'GCGG*UAC'  'GAACAA*UAC'  'GUAAA*UGC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 7 7 7 7 9 8]
            MeanSequenceLength: 7.4286
               DeficitEditData: [13613×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

7 sequences from 3D structures
Using 13613 random sequences, 0 from an alignment, and 7 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 221, IL_55516.2  has acceptance rules AlignmentScore >= -25.6175, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.1175
TP   100.00%, TN    94.07%, min    94.07%,   7 3D sequences,     0 alignment sequences, 13540 random sequences,  803 random matches,  7 NTs, cWW-cWW-cSH-cWW
Sensitivity 100.00%, Specificity  94.07%, Minimum  94.07% using method 11
Number of false positives with core edit > 0 is 803
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_55917.1'
                     Signature: {'cWW-L-cWW-L-L-R'  ''}
                         NumNT: 8
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 7
                      NumFixed: 28
                      OwnScore: -8.2822
                   OwnSequence: {'UAGUGUCCU*AG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 11
            MeanSequenceLength: 11
               DeficitEditData: [6310×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 6310 random sequences, 0 from an alignment, and 1 from 3D structures
Group 222, IL_55917.1  has acceptance rules AlignmentScore >= -28.2822, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.4780
TP   100.00%, TN    96.01%, min    96.01%,   1 3D sequences,     0 alignment sequences, 6310 random sequences,  252 random matches,  8 NTs, cWW-L-cWW-L-L-R
Sensitivity 100.00%, Specificity  96.01%, Minimum  96.01% using method 6
Number of false positives with core edit > 0 is 252
1 * Deficit + 3 * Core Edit <= 18.1958
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_55953.3'
                     Signature: {'cWW-tSH-tHS-R-L-L-R-cWW'  ''}
                         NumNT: 12
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 11
                        NumBPh: 6
                         NumBR: 2
                  NumInstances: 4
                      Truncate: 7
                      NumFixed: 26
                      OwnScore: [-4.4409 -4.4409 -5.2882 -4.4409]
                   OwnSequence: {'GGACCC*GCUAAC'  'GGACCC*GCUAAC'  'GGAACC*GCUAAC'  'GGACCC*GCUAAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [12 12 12 12]
            MeanSequenceLength: 12
               DeficitEditData: [2091×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 2091 random sequences, 0 from an alignment, and 4 from 3D structures
Decreased cutoff from  20.1018 because the cutoff seemed overly generous
Group 223, IL_55953.3  has acceptance rules AlignmentScore >= -24.4409, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.4409
TP   100.00%, TN    96.32%, min    96.32%,   4 3D sequences,     0 alignment sequences, 2091 random sequences,   77 random matches, 12 NTs, cWW-tSH-tHS-R-L-L-R-cWW
Sensitivity 100.00%, Specificity  96.32%, Minimum  96.32% using method 8
Number of false positives with core edit > 0 is 77
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1
Motif index 2
Motif index 3
Motif index 4


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_56317.1'
                     Signature: {'cWW-L-R-L-R-L-cWW'  ''}
                         NumNT: 9
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 2
                      Truncate: 6
                      NumFixed: 34
                      OwnScore: [-6.1986 -6.1986]
                   OwnSequence: {'GGAAUA*UCUUC'  'GGAAUA*UCUUC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11]
            MeanSequenceLength: 11
               DeficitEditData: [9572×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 9572 random sequences, 0 from an alignment, and 2 from 3D structures
Group 224, IL_56317.1  has acceptance rules AlignmentScore >= -26.1986, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.6783
TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 9572 random sequences,  383 random matches,  9 NTs, cWW-L-R-L-R-L-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 383
1 * Deficit + 3 * Core Edit <= 18.4796
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_56455.6'
                     Signature: {'cWW-tSH-tHW-L-R-L-R-L-R-tWH-tHS-cWW'  ''}
                         NumNT: 18
                  NumBasepairs: 8
                    Structured: 1
                     NumStacks: 21
                        NumBPh: 0
                         NumBR: 2
                  NumInstances: 7
                      Truncate: 10
                      NumFixed: 26
                      OwnScore: [-9.6474 -9.6474 -9.6474 -9.6474 -9.7805 -10.7106 -9.6474]
                   OwnSequence: {1×7 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [18 18 18 18 18 18 18]
            MeanSequenceLength: 18
               DeficitEditData: [74×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

7 sequences from 3D structures
Using 74 random sequences, 0 from an alignment, and 7 from 3D structures
Decreased cutoff from  24.5445 because the cutoff seemed overly generous
Group 225, IL_56455.6  has acceptance rules AlignmentScore >= -29.6474, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  33.0703
TP   100.00%, TN    98.65%, min    98.65%,   7 3D sequences,     0 alignment sequences,   74 random sequences,    1 random matches, 18 NTs, cWW-tSH-tHW-L-R-L-R-L-R-tWH-tHS-cWW
Sensitivity 100.00%, Specificity  98.65%, Minimum  98.65% using method 8
Number of false positives with core edit > 0 is 1
1 * Deficit + 3 * Core Edit <= 23.4229
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_56987.1'
                     Signature: {'cWW-L-cWW'  ''}
                         NumNT: 5
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 3
                      Truncate: 4
                      NumFixed: 16
                      OwnScore: [-4.1600 -4.2063 -4.6678]
                   OwnSequence: {'GUUA*UC'  'CUUG*CG'  'GUAC*GC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 6]
            MeanSequenceLength: 6
               DeficitEditData: [8857×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 8857 random sequences, 0 from an alignment, and 3 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 226, IL_56987.1  has acceptance rules AlignmentScore >= -24.1600, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.6600
TP   100.00%, TN    87.11%, min    87.11%,   3 3D sequences,     0 alignment sequences, 8720 random sequences, 1124 random matches,  5 NTs, cWW-L-cWW
Sensitivity 100.00%, Specificity  87.11%, Minimum  87.11% using method 11
Number of false positives with core edit > 0 is 1124
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_57188.5'
                     Signature: {'cWW-tWW-L-tWW-cWW-cSH'  ''}
                         NumNT: 11
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 11
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 5
                      Truncate: 8
                      NumFixed: 32
                      OwnScore: [-7.5027 -6.9424 -6.6464 -6.6464 -8.0905]
                   OwnSequence: {'CUAAGUG*CUUAAG'  'UUAAGUG*CUCAAA'  'UUAAGUG*CUAAA'  'UUAAGUG*CUAAA'  'CUCAGUG*CUCAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [13 13 12 12 13]
            MeanSequenceLength: 12.6000
               DeficitEditData: [2716×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

5 sequences from 3D structures
Using 2716 random sequences, 0 from an alignment, and 5 from 3D structures
Group 227, IL_57188.5  has acceptance rules AlignmentScore >= -26.6464, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.6731
TP   100.00%, TN    95.99%, min    95.99%,   5 3D sequences,     0 alignment sequences, 2716 random sequences,  109 random matches, 11 NTs, cWW-tWW-L-tWW-cWW-cSH
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 109
1 * Deficit + 3 * Core Edit <= 19.0266
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_57741.1'
                     Signature: {'cWW-L-R-L-R-L-R-L-R-L-cWW-L-cWW'  ''}
                         NumNT: 16
                  NumBasepairs: 7
                    Structured: 1
                     NumStacks: 15
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 10
                      NumFixed: 40
                      OwnScore: -10.7017
                   OwnSequence: {'CUUGGAUUUA*UUGUCAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 17
            MeanSequenceLength: 17
               DeficitEditData: [55×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 55 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  20.4606 because the cutoff seemed overly generous
Group 228, IL_57741.1  has acceptance rules AlignmentScore >= -30.7017, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  30.7017
TP   100.00%, TN    96.36%, min    96.36%,   1 3D sequences,     0 alignment sequences,   55 random sequences,    2 random matches, 16 NTs, cWW-L-R-L-R-L-R-L-R-L-cWW-L-cWW
Sensitivity 100.00%, Specificity  96.36%, Minimum  96.36% using method 8
Number of false positives with core edit > 0 is 2
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_57744.1'
                     Signature: {'cWW-cWW-cWW'  ''}
                         NumNT: 6
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 22
                      Truncate: 4
                      NumFixed: 14
                      OwnScore: [-5.5795 -4.9111 -4.9111 -9.1206 -6.2477 -7.1134 -6.5024 -8.5556 -7.7988 -5.5795 -5.7613 -6.0723 -5.3245 … ]
                   OwnSequence: {1×22 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 7 7 7 6 6 7 7 6 7 7 7 7 7 7 7 7 7 7 7 6 7]
            MeanSequenceLength: 6.8182
               DeficitEditData: [7773×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

22 sequences from 3D structures
Using 7773 random sequences, 0 from an alignment, and 22 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 229, IL_57744.1  has acceptance rules AlignmentScore >= -24.9111, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  14.4111
TP   100.00%, TN    83.92%, min    83.92%,  22 3D sequences,     0 alignment sequences, 7287 random sequences, 1172 random matches,  6 NTs, cWW-cWW-cWW
Sensitivity 100.00%, Specificity  83.92%, Minimum  83.92% using method 11
Number of false positives with core edit > 0 is 1172
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11
Motif index 12
Motif index 13
Motif index 14
Motif index 15
Motif index 16
Motif index 17
Motif index 18
Motif index 19
Motif index 20
Motif index 21
Motif index 22


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_57881.1'
                     Signature: {'cWW-L-cWW'  ''}
                         NumNT: 5
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 4
                      NumFixed: 16
                      OwnScore: -6.5784
                   OwnSequence: {'CCAUC*GGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 8
            MeanSequenceLength: 8
               DeficitEditData: [16733×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 16733 random sequences, 0 from an alignment, and 1 from 3D structures
Group 230, IL_57881.1  has acceptance rules AlignmentScore >= -26.5784, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.8959
TP   100.00%, TN    95.98%, min    95.98%,   1 3D sequences,     0 alignment sequences, 16730 random sequences,  672 random matches,  5 NTs, cWW-L-cWW
Sensitivity 100.00%, Specificity  95.98%, Minimum  95.98% using method 6
Number of false positives with core edit > 0 is 672
1 * Deficit + 3 * Core Edit <= 10.3175
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_58103.11'
                     Signature: {'cWW-cSH-cWS-L-tSW-R-R-cWW'  ''}
                         NumNT: 10
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 9
                      Truncate: 6
                      NumFixed: 32
                      OwnScore: [-4.0236 -2.7703 -3.1763 -3.9425 -4.3945 -3.1763 -2.7703 -2.7703 -2.7703]
                   OwnSequence: {1×9 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10 10 10 10 10 10 10 10]
            MeanSequenceLength: 10
               DeficitEditData: [1215×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

9 sequences from 3D structures
Using 1215 random sequences, 0 from an alignment, and 9 from 3D structures
Group 231, IL_58103.11 has acceptance rules AlignmentScore >= -22.7703, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  18.9624
TP   100.00%, TN    95.97%, min    95.97%,   9 3D sequences,     0 alignment sequences, 1215 random sequences,   49 random matches, 10 NTs, cWW-cSH-cWS-L-tSW-R-R-cWW
Sensitivity 100.00%, Specificity  95.97%, Minimum  95.97% using method 6
Number of false positives with core edit > 0 is 49
1 * Deficit + 3 * Core Edit <= 16.1921
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_58112.2'
                     Signature: {'cWW-cWW-L-R-cWW'  ''}
                         NumNT: 8
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 4
                      Truncate: 5
                      NumFixed: 16
                      OwnScore: [-7.0700 -7.2193 -7.4149 -11.6680]
                   OwnSequence: {'GGGC*GGUAC'  'GAAG*CCUGC'  'GGAC*GAAAC'  'UUUCC*GACAA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 9 10]
            MeanSequenceLength: 9.2500
               DeficitEditData: [11536×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 11536 random sequences, 0 from an alignment, and 4 from 3D structures
Group 232, IL_58112.2  has acceptance rules AlignmentScore >= -27.0700, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.8058
TP   100.00%, TN    95.99%, min    95.99%,   4 3D sequences,     0 alignment sequences, 11526 random sequences,  462 random matches,  8 NTs, cWW-cWW-L-R-cWW
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 462
1 * Deficit + 3 * Core Edit <= 9.7359
Motif index 1
Motif index 2
Motif index 3
Motif index 4


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_58126.1'
                     Signature: {'cWW-L-R-L-R-L-R-L-R-L-R-L-cWW'  ''}
                         NumNT: 15
                  NumBasepairs: 7
                    Structured: 1
                     NumStacks: 15
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 9
                      NumFixed: 26
                      OwnScore: [-13.2359 -11.4192]
                   OwnSequence: {'CACGAAUU*ACAGAUG'  'GGAUAAAUC*GGAAUAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [15 16]
            MeanSequenceLength: 15.5000
               DeficitEditData: [1662×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 1662 random sequences, 0 from an alignment, and 2 from 3D structures
Decreased cutoff from  20.8016 because the cutoff seemed overly generous
Group 233, IL_58126.1  has acceptance rules AlignmentScore >= -31.4192, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  31.4192
TP   100.00%, TN    97.47%, min    97.47%,   2 3D sequences,     0 alignment sequences, 1662 random sequences,   42 random matches, 15 NTs, cWW-L-R-L-R-L-R-L-R-L-R-L-cWW
Sensitivity 100.00%, Specificity  97.47%, Minimum  97.47% using method 8
Number of false positives with core edit > 0 is 42
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_58350.1'
                     Signature: {'cWW-L-R-tWH-tWH-L-R-L-cWW-L'  ''}
                         NumNT: 14
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 11
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 9
                      NumFixed: 34
                      OwnScore: -8.2231
                   OwnSequence: {'GGACAAAG*UUAAAUC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 15
            MeanSequenceLength: 15
               DeficitEditData: [1298×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 1298 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  22.5430 because the cutoff seemed overly generous
Group 234, IL_58350.1  has acceptance rules AlignmentScore >= -28.2231, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  29.3702
TP   100.00%, TN    98.00%, min    98.00%,   1 3D sequences,     0 alignment sequences, 1298 random sequences,   26 random matches, 14 NTs, cWW-L-R-tWH-tWH-L-R-L-cWW-L
Sensitivity 100.00%, Specificity  98.00%, Minimum  98.00% using method 8
Number of false positives with core edit > 0 is 26
1 * Deficit + 3 * Core Edit <= 21.1471
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_58960.1'
                     Signature: {'cWW-L-cWW-L-tWW-L-R-L'  ''}
                         NumNT: 11
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 3
                      Truncate: 10
                      NumFixed: 32
                      OwnScore: [-6.1288 -6.1288 -7.2086]
                   OwnSequence: {'UAAAGAGUG*CA'  'UAAAGAGUG*CA'  'AAAAGCAUG*CU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11 11]
            MeanSequenceLength: 11
               DeficitEditData: [4868×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 4868 random sequences, 0 from an alignment, and 3 from 3D structures
Group 235, IL_58960.1  has acceptance rules AlignmentScore >= -26.1288, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  23.5416
TP   100.00%, TN    95.99%, min    95.99%,   3 3D sequences,     0 alignment sequences, 4867 random sequences,  195 random matches, 11 NTs, cWW-L-cWW-L-tWW-L-R-L
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 195
1 * Deficit + 3 * Core Edit <= 17.4128
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_59049.1'
                     Signature: {'cWW-cWW-L-R-L-R-L-R-L-R-L-cWW-L'  ''}
                         NumNT: 16
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 11
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 10
                      NumFixed: 48
                      OwnScore: [-8.8977 -8.8977]
                   OwnSequence: {'GAAAAAAUU*AUAUUAGC'  'GAAAAAAUU*AUAUUAGC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [17 17]
            MeanSequenceLength: 17
               DeficitEditData: [315×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 315 random sequences, 0 from an alignment, and 2 from 3D structures
Decreased cutoff from  22.8595 because the cutoff seemed overly generous
Group 236, IL_59049.1  has acceptance rules AlignmentScore >= -28.8977, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  30.7004
TP   100.00%, TN    98.10%, min    98.10%,   2 3D sequences,     0 alignment sequences,  315 random sequences,    6 random matches, 16 NTs, cWW-cWW-L-R-L-R-L-R-L-R-L-cWW-L
Sensitivity 100.00%, Specificity  98.10%, Minimum  98.10% using method 8
Number of false positives with core edit > 0 is 6
1 * Deficit + 3 * Core Edit <= 21.8028
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_59258.1'
                     Signature: {'cWW-L-R-L-R-L-cWW-L-cWW'  ''}
                         NumNT: 12
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 8
                      NumFixed: 32
                      OwnScore: -7.5992
                   OwnSequence: {'GAUGAAA*UAACC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 12
            MeanSequenceLength: 12
               DeficitEditData: [7089×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 7089 random sequences, 0 from an alignment, and 1 from 3D structures
Group 237, IL_59258.1  has acceptance rules AlignmentScore >= -27.5992, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.8665
TP   100.00%, TN    95.98%, min    95.98%,   1 3D sequences,     0 alignment sequences, 7089 random sequences,  285 random matches, 12 NTs, cWW-L-R-L-R-L-cWW-L-cWW
Sensitivity 100.00%, Specificity  95.98%, Minimum  95.98% using method 6
Number of false positives with core edit > 0 is 285
1 * Deficit + 3 * Core Edit <= 19.2673
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_59302.1'
                     Signature: {'cWW-L-R-L-cWW-L'  ''}
                         NumNT: 9
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 7
                      NumFixed: 32
                      OwnScore: [-6.4258 -6.4258]
                   OwnSequence: {'UACAAG*CGA'  'UACCAG*CAA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9]
            MeanSequenceLength: 9
               DeficitEditData: [16609×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 16609 random sequences, 0 from an alignment, and 2 from 3D structures
Group 238, IL_59302.1  has acceptance rules AlignmentScore >= -26.4258, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  19.7433
TP   100.00%, TN    95.98%, min    95.98%,   2 3D sequences,     0 alignment sequences, 16609 random sequences,  668 random matches,  9 NTs, cWW-L-R-L-cWW-L
Sensitivity 100.00%, Specificity  95.98%, Minimum  95.98% using method 6
Number of false positives with core edit > 0 is 668
1 * Deficit + 3 * Core Edit <= 13.3175
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_59724.1'
                     Signature: {'cWW-L-R-L-R-cSH-tWH-tHS-R-L-cWW'  ''}
                         NumNT: 15
                  NumBasepairs: 8
                    Structured: 1
                     NumStacks: 16
                        NumBPh: 3
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 9
                      NumFixed: 28
                      OwnScore: -6.2989
                   OwnSequence: {'CCAGUACG*CCGACCG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 15
            MeanSequenceLength: 15
               DeficitEditData: [106×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 106 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  23.4100 because the cutoff seemed overly generous
Group 239, IL_59724.1  has acceptance rules AlignmentScore >= -26.2989, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.9746
TP   100.00%, TN    98.11%, min    98.11%,   1 3D sequences,     0 alignment sequences,  106 random sequences,    2 random matches, 15 NTs, cWW-L-R-L-R-cSH-tWH-tHS-R-L-cWW
Sensitivity 100.00%, Specificity  98.11%, Minimum  98.11% using method 8
Number of false positives with core edit > 0 is 2
1 * Deficit + 3 * Core Edit <= 20.6757
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_59877.1'
                     Signature: {'cWW-L-cWW'  ''}
                         NumNT: 5
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 2
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 4
                      NumFixed: 22
                      OwnScore: [-2.8610 -3.6873]
                   OwnSequence: {'GAUC*GC'  'UAUA*UG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6]
            MeanSequenceLength: 6
               DeficitEditData: [8798×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 8798 random sequences, 0 from an alignment, and 2 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 240, IL_59877.1  has acceptance rules AlignmentScore >= -22.8610, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  12.3610
TP   100.00%, TN    93.21%, min    93.21%,   2 3D sequences,     0 alignment sequences, 8745 random sequences,  594 random matches,  5 NTs, cWW-L-cWW
Sensitivity 100.00%, Specificity  93.21%, Minimum  93.21% using method 11
Number of false positives with core edit > 0 is 594
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_60448.1'
                     Signature: {'cWW-L-cWW-L-R-L-tWH-L-tHS-L-R-L-cWW-L-R'  ''}
                         NumNT: 20
                  NumBasepairs: 7
                    Structured: 1
                     NumStacks: 15
                        NumBPh: 2
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 14
                      NumFixed: 54
                      OwnScore: -10.0383
                   OwnSequence: {'GGAGCGCUGCAAG*CCCAGGC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 20
            MeanSequenceLength: 20
               DeficitEditData: [2×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 2 random sequences, 0 from an alignment, and 1 from 3D structures
Group 241, IL_60448.1  has acceptance rules AlignmentScore >= -30.0383, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  35.0383
TP   100.00%, TN    50.00%, min    50.00%,   1 3D sequences,     0 alignment sequences,    2 random sequences,    1 random matches, 20 NTs, cWW-L-cWW-L-R-L-tWH-L-tHS-L-R-L-cWW-L-R
Sensitivity 100.00%, Specificity  50.00%, Minimum  50.00% using method 1
Number of false positives with core edit > 0 is 1
1 * Deficit + 3 * Core Edit <= 25.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_60657.1'
                     Signature: {'cWW-cWW-L-R-L-cWW-L-L-R-L-R-L-R'  ''}
                         NumNT: 16
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 13
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 13
                      NumFixed: 54
                      OwnScore: -10.5146
                   OwnSequence: {'CUGGCGGAUUAG*CGUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 16
            MeanSequenceLength: 16
               DeficitEditData: [309×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 309 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  20.0358 because the cutoff seemed overly generous
Group 242, IL_60657.1  has acceptance rules AlignmentScore >= -30.5146, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  30.5146
TP   100.00%, TN    96.12%, min    96.12%,   1 3D sequences,     0 alignment sequences,  309 random sequences,   12 random matches, 16 NTs, cWW-cWW-L-R-L-cWW-L-L-R-L-R-L-R
Sensitivity 100.00%, Specificity  96.12%, Minimum  96.12% using method 8
Number of false positives with core edit > 0 is 12
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_60797.1'
                     Signature: {'cWW-cWW-tSH-tHW-tHW-L-R-L-cWW-cWW'  ''}
                         NumNT: 17
                  NumBasepairs: 8
                    Structured: 1
                     NumStacks: 15
                        NumBPh: 1
                         NumBR: 2
                  NumInstances: 4
                      Truncate: 10
                      NumFixed: 28
                      OwnScore: [-9.5598 -11.6931 -9.5598 -10.4071]
                   OwnSequence: {'GAGAAACAC*GGUACAUUACC'  'GAGAAACAC*GGUCCAUUACC'  'GAGAAACAC*GGUACAUUACC'  'GAGAAACAC*GGUAUAUUACC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [20 20 20 20]
            MeanSequenceLength: 20
               DeficitEditData: [15×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 15 random sequences, 0 from an alignment, and 4 from 3D structures
Group 243, IL_60797.1  has acceptance rules AlignmentScore >= -29.5598, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  34.5598
TP   100.00%, TN   100.00%, min   100.00%,   4 3D sequences,     0 alignment sequences,   15 random sequences,    0 random matches, 17 NTs, cWW-cWW-tSH-tHW-tHW-L-R-L-cWW-cWW
Sensitivity 100.00%, Specificity 100.00%, Minimum 100.00% using method 1
Number of false positives with core edit > 0 is 0
1 * Deficit + 3 * Core Edit <= 25.0000
Motif index 1
Motif index 2
Motif index 3
Motif index 4


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_61242.1'
                     Signature: {'cWW-cWW-L-R-L-R-cWW'  ''}
                         NumNT: 10
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 0
                         NumBR: 2
                  NumInstances: 1
                      Truncate: 6
                      NumFixed: 24
                      OwnScore: -5.2390
                   OwnSequence: {'CUGUG*CUGUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 10
            MeanSequenceLength: 10
               DeficitEditData: [5339×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 5339 random sequences, 0 from an alignment, and 1 from 3D structures
Group 244, IL_61242.1  has acceptance rules AlignmentScore >= -25.2390, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  23.4982
TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences, 5339 random sequences,  214 random matches, 10 NTs, cWW-cWW-L-R-L-R-cWW
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 214
1 * Deficit + 3 * Core Edit <= 18.2592
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_61249.1'
                     Signature: {'cWW-L-R-L-R-tHS-cWW-cWW-tSH-tHS-cWW-cWW'  ''}
                         NumNT: 20
                  NumBasepairs: 9
                    Structured: 1
                     NumStacks: 19
                        NumBPh: 2
                         NumBR: 5
                  NumInstances: 1
                      Truncate: 11
                      NumFixed: 34
                      OwnScore: -10.8617
                   OwnSequence: {'UUAAUUGAUG*UUGAUCGAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 20
            MeanSequenceLength: 20
               DeficitEditData: [4×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 4 random sequences, 0 from an alignment, and 1 from 3D structures
Group 245, IL_61249.1  has acceptance rules AlignmentScore >= -30.8617, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  35.8617
TP   100.00%, TN   100.00%, min   100.00%,   1 3D sequences,     0 alignment sequences,    4 random sequences,    0 random matches, 20 NTs, cWW-L-R-L-R-tHS-cWW-cWW-tSH-tHS-cWW-cWW
Sensitivity 100.00%, Specificity 100.00%, Minimum 100.00% using method 1
Number of false positives with core edit > 0 is 0
1 * Deficit + 3 * Core Edit <= 25.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_61258.15'
                     Signature: {'cWW-L-cWW'  ''}
                         NumNT: 5
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 41
                      Truncate: 4
                      NumFixed: 16
                      OwnScore: [-3.4083 -3.4083 -3.1941 -3.4083 -3.3629 -2.8255 -2.5432 -2.7761 -2.5432 -2.8255 -3.0584 -2.7761 -2.5432 … ]
                   OwnSequence: {1×41 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5]
            MeanSequenceLength: 5
               DeficitEditData: [4697×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

41 sequences from 3D structures
Using 4697 random sequences, 0 from an alignment, and 41 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 246, IL_61258.15 has acceptance rules AlignmentScore >= -22.5432, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  12.0432
TP   100.00%, TN    85.87%, min    85.87%,  41 3D sequences,     0 alignment sequences, 4559 random sequences,  644 random matches,  5 NTs, cWW-L-cWW
Sensitivity 100.00%, Specificity  85.87%, Minimum  85.87% using method 11
Number of false positives with core edit > 0 is 644
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11
Motif index 12
Motif index 13
Motif index 14
Motif index 15
Motif index 16
Motif index 17
Motif index 18
Motif index 19
Motif index 20
Motif index 21
Motif index 22
Motif index 23
Motif index 24
Motif index 25
Motif index 26
Motif index 27
Motif index 28
Motif index 29
Motif index 30
Motif index 31
Motif index 32
Motif index 33
Motif index 34
Motif index 35
Motif index 36
Motif index 37
Motif index 38
Motif index 39
Motif index 40
Motif index 41


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_61286.1'
                     Signature: {'cWW-L-R-L-R-L-tWH-L-tHS-cWW'  ''}
                         NumNT: 14
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 3
                         NumBR: 3
                  NumInstances: 1
                      Truncate: 9
                      NumFixed: 34
                      OwnScore: -7.6353
                   OwnSequence: {'CAUAGUAC*GGAAGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 14
            MeanSequenceLength: 14
               DeficitEditData: [2677×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 2677 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  22.3217 because the cutoff seemed overly generous
Group 247, IL_61286.1  has acceptance rules AlignmentScore >= -27.6353, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  27.6353
TP   100.00%, TN    97.98%, min    97.98%,   1 3D sequences,     0 alignment sequences, 2677 random sequences,   54 random matches, 14 NTs, cWW-L-R-L-R-L-tWH-L-tHS-cWW
Sensitivity 100.00%, Specificity  97.98%, Minimum  97.98% using method 8
Number of false positives with core edit > 0 is 54
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_61299.4'
                     Signature: {'cWW-L-R-L-cWW-L-L'  ''}
                         NumNT: 9
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 3
                      Truncate: 7
                      NumFixed: 28
                      OwnScore: [-5.9841 -5.9841 -7.6616]
                   OwnSequence: {'UCUAAG*CUG'  'UCUAAG*CUG'  'CGGAAA*UGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 9]
            MeanSequenceLength: 9
               DeficitEditData: [8390×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 8390 random sequences, 0 from an alignment, and 3 from 3D structures
Group 248, IL_61299.4  has acceptance rules AlignmentScore >= -25.9841, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  18.6389
TP   100.00%, TN    95.98%, min    95.98%,   3 3D sequences,     0 alignment sequences, 8384 random sequences,  337 random matches,  9 NTs, cWW-L-R-L-cWW-L-L
Sensitivity 100.00%, Specificity  95.98%, Minimum  95.98% using method 6
Number of false positives with core edit > 0 is 337
1 * Deficit + 3 * Core Edit <= 12.6547
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_61341.1'
                     Signature: {'cWW-L-R-L-cWW'  ''}
                         NumNT: 6
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 4
                      NumFixed: 14
                      OwnScore: [-7.5419 -6.9381]
                   OwnSequence: {'CGAAG*CAG'  'UUGU*ACG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 7]
            MeanSequenceLength: 7.5000
               DeficitEditData: [13873×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 13873 random sequences, 0 from an alignment, and 2 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 249, IL_61341.1  has acceptance rules AlignmentScore >= -26.9381, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.4381
TP   100.00%, TN    90.37%, min    90.37%,   2 3D sequences,     0 alignment sequences, 13847 random sequences, 1334 random matches,  6 NTs, cWW-L-R-L-cWW
Sensitivity 100.00%, Specificity  90.37%, Minimum  90.37% using method 11
Number of false positives with core edit > 0 is 1334
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_61438.4'
                     Signature: {'cWW-L-cWW'  ''}
                         NumNT: 5
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 2
                  NumInstances: 4
                      Truncate: 4
                      NumFixed: 16
                      OwnScore: [-2.7299 -2.7299 -2.7299 -2.7299]
                   OwnSequence: {'CAAG*CCG'  'CAAG*CCG'  'CAAG*CCG'  'CAAG*CCG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 7 7 7]
            MeanSequenceLength: 7
               DeficitEditData: [9011×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 9011 random sequences, 0 from an alignment, and 4 from 3D structures
Group 250, IL_61438.4  has acceptance rules AlignmentScore >= -22.7299, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.5137
TP   100.00%, TN    96.00%, min    96.00%,   4 3D sequences,     0 alignment sequences, 8997 random sequences,  360 random matches,  5 NTs, cWW-L-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 360
1 * Deficit + 3 * Core Edit <= 10.7838
Motif index 1
Motif index 2
Motif index 3
Motif index 4


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_61440.1'
                     Signature: {'cWW-tSH-tHS-tWS-cWW'  ''}
                         NumNT: 10
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 0
                         NumBR: 2
                  NumInstances: 1
                      Truncate: 6
                      NumFixed: 18
                      OwnScore: -6.9696
                   OwnSequence: {'CGAAG*UGGAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 10
            MeanSequenceLength: 10
               DeficitEditData: [5217×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 5217 random sequences, 0 from an alignment, and 1 from 3D structures
Group 251, IL_61440.1  has acceptance rules AlignmentScore >= -26.9696, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  20.0062
TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences, 5214 random sequences,  209 random matches, 10 NTs, cWW-tSH-tHS-tWS-cWW
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 209
1 * Deficit + 3 * Core Edit <= 13.0366
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_61476.2'
                     Signature: {'cWW-tSH-L-cWW-L'  ''}
                         NumNT: 8
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 7
                      Truncate: 6
                      NumFixed: 22
                      OwnScore: [-6.1278 -5.6170 -5.9845 -5.0301 -5.0301 -5.1249 -7.3225]
                   OwnSequence: {'CGAAG*CAG'  'CGGAG*CAG'  'CAUAG*CAG'  'AGUAG*CAU'  'AGUAG*CAU'  'UGUAG*CAA'  'AGGUU*AAU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8 8 8 8 8 8]
            MeanSequenceLength: 8
               DeficitEditData: [11032×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

7 sequences from 3D structures
Using 11032 random sequences, 0 from an alignment, and 7 from 3D structures
Group 252, IL_61476.2  has acceptance rules AlignmentScore >= -25.0301, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.9213
TP   100.00%, TN    95.99%, min    95.99%,   7 3D sequences,     0 alignment sequences, 10987 random sequences,  441 random matches,  8 NTs, cWW-tSH-L-cWW-L
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 441
1 * Deficit + 3 * Core Edit <= 10.8912
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_62012.1'
                     Signature: {'cWW-cWW-L-R-L-cWW'  ''}
                         NumNT: 9
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 6
                      NumFixed: 26
                      OwnScore: -6.3787
                   OwnSequence: {'AAAAG*CGCU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 9
            MeanSequenceLength: 9
               DeficitEditData: [12644×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 12644 random sequences, 0 from an alignment, and 1 from 3D structures
Group 253, IL_62012.1  has acceptance rules AlignmentScore >= -26.3787, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  19.8347
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 12641 random sequences,  506 random matches,  9 NTs, cWW-cWW-L-R-L-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 506
1 * Deficit + 3 * Core Edit <= 13.4561
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_62654.1'
                     Signature: {'cWW-tSH-tHH-tHS-cWW'  ''}
                         NumNT: 10
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 1
                         NumBR: 2
                  NumInstances: 1
                      Truncate: 6
                      NumFixed: 18
                      OwnScore: -8.3930
                   OwnSequence: {'CGAAC*GCAUAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 11
            MeanSequenceLength: 11
               DeficitEditData: [7733×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 7733 random sequences, 0 from an alignment, and 1 from 3D structures
Group 254, IL_62654.1  has acceptance rules AlignmentScore >= -28.3930, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  23.3258
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 7733 random sequences,  309 random matches, 10 NTs, cWW-tSH-tHH-tHS-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 309
1 * Deficit + 3 * Core Edit <= 14.9328
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_63519.1'
                     Signature: {'cWW-cWW-L-R-cSH-cWW'  ''}
                         NumNT: 9
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 2
                      Truncate: 6
                      NumFixed: 22
                      OwnScore: [-6.3177 -6.3177]
                   OwnSequence: {'GAUAC*GCAGC'  'GAUAC*GCAGC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10]
            MeanSequenceLength: 10
               DeficitEditData: [7013×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 7013 random sequences, 0 from an alignment, and 2 from 3D structures
Group 255, IL_63519.1  has acceptance rules AlignmentScore >= -26.3177, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  21.8717
TP   100.00%, TN    95.99%, min    95.99%,   2 3D sequences,     0 alignment sequences, 7013 random sequences,  281 random matches,  9 NTs, cWW-cWW-L-R-cSH-cWW
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 281
1 * Deficit + 3 * Core Edit <= 15.5541
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_63596.11'
                     Signature: {'cWW-cWS-cSH-tWH-cWW-L'  ''}
                         NumNT: 7
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 19
                      Truncate: 6
                      NumFixed: 26
                      OwnScore: [-6.4143 -5.4776 -3.4810 -3.4810 -3.4810 -4.7265 -7.1993 -3.3559 -3.3559 -9.1433 -5.0366 -3.3559 -9.1433 … ]
                   OwnSequence: {1×19 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8 8 8 8 8 8 8 8 9 8 8 9 8 8 8 8 8 8]
            MeanSequenceLength: 8.1053
               DeficitEditData: [4912×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

19 sequences from 3D structures
Using 4912 random sequences, 0 from an alignment, and 19 from 3D structures
Group 256, IL_63596.11 has acceptance rules AlignmentScore >= -23.3559, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.6045
TP   100.00%, TN    95.98%, min    95.98%,  19 3D sequences,     0 alignment sequences, 4898 random sequences,  197 random matches,  7 NTs, cWW-cWS-cSH-tWH-cWW-L
Sensitivity 100.00%, Specificity  95.98%, Minimum  95.98% using method 6
Number of false positives with core edit > 0 is 197
1 * Deficit + 3 * Core Edit <= 12.2486
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11
Motif index 12
Motif index 13
Motif index 14
Motif index 15
Motif index 16
Motif index 17
Motif index 18
Motif index 19


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_63775.1'
                     Signature: {'cWW-L-cWW'  ''}
                         NumNT: 5
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 4
                      NumFixed: 18
                      OwnScore: -3.1649
                   OwnSequence: {'CCG*CG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 5
            MeanSequenceLength: 5
               DeficitEditData: [5514×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 5514 random sequences, 0 from an alignment, and 1 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 257, IL_63775.1  has acceptance rules AlignmentScore >= -23.1649, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  12.6649
TP   100.00%, TN    82.29%, min    82.29%,   1 3D sequences,     0 alignment sequences, 5376 random sequences,  952 random matches,  5 NTs, cWW-L-cWW
Sensitivity 100.00%, Specificity  82.29%, Minimum  82.29% using method 11
Number of false positives with core edit > 0 is 952
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_64048.1'
                     Signature: {'cWW-L-cWW-L-L-tWH-R-L-R'  ''}
                         NumNT: 11
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 10
                      NumFixed: 32
                      OwnScore: [-6.0564 -6.0564]
                   OwnSequence: {'CCGAAGCGAG*UG'  'CCGAAGCGAG*UG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [12 12]
            MeanSequenceLength: 12
               DeficitEditData: [3417×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 3417 random sequences, 0 from an alignment, and 2 from 3D structures
Decreased cutoff from  20.8887 because the cutoff seemed overly generous
Group 258, IL_64048.1  has acceptance rules AlignmentScore >= -26.0564, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.0564
TP   100.00%, TN    97.40%, min    97.40%,   2 3D sequences,     0 alignment sequences, 3417 random sequences,   89 random matches, 11 NTs, cWW-L-cWW-L-L-tWH-R-L-R
Sensitivity 100.00%, Specificity  97.40%, Minimum  97.40% using method 8
Number of false positives with core edit > 0 is 89
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_64231.5'
                     Signature: {'cWW-cWW-L-R-L-cWW'  ''}
                         NumNT: 9
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 11
                      Truncate: 6
                      NumFixed: 26
                      OwnScore: [-6.8220 -8.5566 -7.6403 -7.6403 -8.7301 -7.0901 -6.6789 -10.4670 -11.6222 -9.5898 -7.0901]
                   OwnSequence: {1×11 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 9 9 9 9 9 9 9 9 9]
            MeanSequenceLength: 9
               DeficitEditData: [11699×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

11 sequences from 3D structures
Using 11699 random sequences, 0 from an alignment, and 11 from 3D structures
Group 259, IL_64231.5  has acceptance rules AlignmentScore >= -26.6789, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.4972
TP   100.00%, TN    96.00%, min    96.00%,  11 3D sequences,     0 alignment sequences, 11689 random sequences,  468 random matches,  9 NTs, cWW-cWW-L-R-L-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 468
1 * Deficit + 3 * Core Edit <= 9.8183
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_64403.1'
                     Signature: {'cWW-L-R-L-R-L-R-L-cWW-L-L-R'  ''}
                         NumNT: 14
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 11
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 10
                      NumFixed: 46
                      OwnScore: -10.3733
                   OwnSequence: {'UGUGCCAAUGG*CAAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 16
            MeanSequenceLength: 16
               DeficitEditData: [510×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 510 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  21.7783 because the cutoff seemed overly generous
Group 260, IL_64403.1  has acceptance rules AlignmentScore >= -30.3733, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  30.3733
TP   100.00%, TN    98.04%, min    98.04%,   1 3D sequences,     0 alignment sequences,  510 random sequences,   10 random matches, 14 NTs, cWW-L-R-L-R-L-R-L-cWW-L-L-R
Sensitivity 100.00%, Specificity  98.04%, Minimum  98.04% using method 8
Number of false positives with core edit > 0 is 10
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_64842.1'
                     Signature: {'cWW-L-tWH-L-cWW-L-cSH'  ''}
                         NumNT: 10
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 1
                         NumBR: 2
                  NumInstances: 1
                      Truncate: 8
                      NumFixed: 32
                      OwnScore: -6.4917
                   OwnSequence: {'CACUACAC*GAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 11
            MeanSequenceLength: 11
               DeficitEditData: [8375×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 8375 random sequences, 0 from an alignment, and 1 from 3D structures
Group 261, IL_64842.1  has acceptance rules AlignmentScore >= -26.4917, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.4639
TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences, 8375 random sequences,  336 random matches, 10 NTs, cWW-L-tWH-L-cWW-L-cSH
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 336
1 * Deficit + 3 * Core Edit <= 18.9722
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_64858.3'
                     Signature: {'cWW-cHW-cWH-R-L-cWH-cHW-cHW-cWH-cWH-cHW-L-cWW-L-R-cWW-L-cWW'  ''}
                         NumNT: 22
                  NumBasepairs: 14
                    Structured: 1
                     NumStacks: 25
                        NumBPh: 1
                         NumBR: 4
                  NumInstances: 6
                      Truncate: 13
                      NumFixed: 52
                      OwnScore: [-9.7671 -9.7671 -9.1793 -9.3055 -10.7902 -9.3055]
                   OwnSequence: {1×6 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [25 25 25 25 25 25]
            MeanSequenceLength: 25
               DeficitEditData: [0×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

6 sequences from 3D structures
Using 0 random sequences, 0 from an alignment, and 6 from 3D structures
No random sequence matches, so essentially no model-specific cutoff imposed
Decreased cutoff to  25.0000 so that it is possible to reject matches
Group 262, IL_64858.3  has acceptance rules AlignmentScore >= -29.1793, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  34.1793
TP   100.00%, TN      NaN%, min   100.00%,   6 3D sequences,     0 alignment sequences,    0 random sequences,    0 random matches, 22 NTs, cWW-cHW-cWH-R-L-cWH-cHW-cHW-cWH-cWH-cHW-L-cWW-L-R-cWW-L-cWW
Sensitivity 100.00%, Specificity    NaN%, Minimum 100.00% using method 12
Number of false positives with core edit > 0 is 0
1 * Deficit + 3 * Core Edit <= 25.0000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_64900.1'
                     Signature: {'cWW-cWW-tSS-tSH-L-tHS-R-cWW-L'  ''}
                         NumNT: 14
                  NumBasepairs: 7
                    Structured: 1
                     NumStacks: 13
                        NumBPh: 1
                         NumBR: 5
                  NumInstances: 3
                      Truncate: 9
                      NumFixed: 30
                      OwnScore: [-7.4899 -7.4899 -7.4899]
                   OwnSequence: {'CCGAUGAAU*AUGAAG'  'CCGAUGAAU*AUGAAG'  'CCGAUGAAU*AUGAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [15 15 15]
            MeanSequenceLength: 15
               DeficitEditData: [645×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 645 random sequences, 0 from an alignment, and 3 from 3D structures
Decreased cutoff from  22.9820 because the cutoff seemed overly generous
Group 263, IL_64900.1  has acceptance rules AlignmentScore >= -27.4899, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  27.9362
TP   100.00%, TN    97.98%, min    97.98%,   3 3D sequences,     0 alignment sequences,  645 random sequences,   13 random matches, 14 NTs, cWW-cWW-tSS-tSH-L-tHS-R-cWW-L
Sensitivity 100.00%, Specificity  97.98%, Minimum  97.98% using method 8
Number of false positives with core edit > 0 is 13
1 * Deficit + 3 * Core Edit <= 20.4463
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_65594.1'
                     Signature: {'cWW-L-R-tSW-tHH-cSH-tWH-tHS-cWW'  ''}
                         NumNT: 15
                  NumBasepairs: 8
                    Structured: 1
                     NumStacks: 16
                        NumBPh: 3
                         NumBR: 1
                  NumInstances: 2
                      Truncate: 9
                      NumFixed: 28
                      OwnScore: [-8.6488 -8.2587]
                   OwnSequence: {'CUUAGUAA*UGAAGCG'  'CUCAGUAG*UGAAGCG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [15 15]
            MeanSequenceLength: 15
               DeficitEditData: [461×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 461 random sequences, 0 from an alignment, and 2 from 3D structures
Decreased cutoff from  21.3122 because the cutoff seemed overly generous
Group 264, IL_65594.1  has acceptance rules AlignmentScore >= -28.2587, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  28.2587
TP   100.00%, TN    97.83%, min    97.83%,   2 3D sequences,     0 alignment sequences,  461 random sequences,   10 random matches, 15 NTs, cWW-L-R-tSW-tHH-cSH-tWH-tHS-cWW
Sensitivity 100.00%, Specificity  97.83%, Minimum  97.83% using method 8
Number of false positives with core edit > 0 is 10
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_65653.1'
                     Signature: {'cWW-tSW-tHW-tWW-tWH-cSH-L-L-tHS-L-cWW-L'  ''}
                         NumNT: 16
                  NumBasepairs: 8
                    Structured: 1
                     NumStacks: 12
                        NumBPh: 1
                         NumBR: 3
                  NumInstances: 4
                      Truncate: 11
                      NumFixed: 40
                      OwnScore: [-7.6613 -7.6618 -7.6618 -7.6613]
                   OwnSequence: {'GAUUGUAAACAG*CGACAC'  'GAUUGUAAACAU*AGACAC'  'GAUUGUAAACAU*AGACAC'  'GAUUGUAAACAG*CGACAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [18 18 18 18]
            MeanSequenceLength: 18
               DeficitEditData: [34×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 34 random sequences, 0 from an alignment, and 4 from 3D structures
Decreased cutoff from  23.7096 because the cutoff seemed overly generous
Group 265, IL_65653.1  has acceptance rules AlignmentScore >= -27.6613, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  28.0928
TP   100.00%, TN    97.06%, min    97.06%,   4 3D sequences,     0 alignment sequences,   34 random sequences,    1 random matches, 16 NTs, cWW-tSW-tHW-tWW-tWH-cSH-L-L-tHS-L-cWW-L
Sensitivity 100.00%, Specificity  97.06%, Minimum  97.06% using method 8
Number of false positives with core edit > 0 is 1
1 * Deficit + 3 * Core Edit <= 20.4315
Motif index 1
Motif index 2
Motif index 3
Motif index 4


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_65718.4'
                     Signature: {'cWW-cSH-cWS-cWW-cWW'  ''}
                         NumNT: 9
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 4
                      Truncate: 6
                      NumFixed: 22
                      OwnScore: [-5.7065 -5.7065 -5.7065 -5.7065]
                   OwnSequence: {'GUAAC*GCCC'  'GUAAC*GCCC'  'GUAAC*GCCC'  'GUAAC*GCCC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 9 9]
            MeanSequenceLength: 9
               DeficitEditData: [7010×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 7010 random sequences, 0 from an alignment, and 4 from 3D structures
Group 266, IL_65718.4  has acceptance rules AlignmentScore >= -25.7065, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  21.0483
TP   100.00%, TN    96.01%, min    96.01%,   4 3D sequences,     0 alignment sequences, 7010 random sequences,  280 random matches,  9 NTs, cWW-cSH-cWS-cWW-cWW
Sensitivity 100.00%, Specificity  96.01%, Minimum  96.01% using method 6
Number of false positives with core edit > 0 is 280
1 * Deficit + 3 * Core Edit <= 15.3419
Motif index 1
Motif index 2
Motif index 3
Motif index 4


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_65851.3'
                     Signature: {'cWW-cWW-cWW-cWW-R-tHW-tSH-tHS-L'  ''}
                         NumNT: 14
                  NumBasepairs: 8
                    Structured: 1
                     NumStacks: 13
                        NumBPh: 2
                         NumBR: 1
                  NumInstances: 2
                      Truncate: 8
                      NumFixed: 28
                      OwnScore: [-5.7492 -5.7492]
                   OwnSequence: {'GCCAGGC*GAGCAAC'  'GCCAGGC*GAGCAAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [14 14]
            MeanSequenceLength: 14
               DeficitEditData: [227×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 227 random sequences, 0 from an alignment, and 2 from 3D structures
Decreased cutoff from  22.0511 because the cutoff seemed overly generous
Group 267, IL_65851.3  has acceptance rules AlignmentScore >= -25.7492, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.7492
TP   100.00%, TN    97.36%, min    97.36%,   2 3D sequences,     0 alignment sequences,  227 random sequences,    6 random matches, 14 NTs, cWW-cWW-cWW-cWW-R-tHW-tSH-tHS-L
Sensitivity 100.00%, Specificity  97.36%, Minimum  97.36% using method 8
Number of false positives with core edit > 0 is 6
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_66635.5'
                     Signature: {'cWW-L-cWW'  ''}
                         NumNT: 5
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 27
                      Truncate: 4
                      NumFixed: 16
                      OwnScore: [-10.4799 -5.8546 -6.0389 -5.5966 -7.7037 -5.7706 -6.5108 -6.7635 -5.0073 -7.0630 -5.1066 -6.1276 … ]
                   OwnSequence: {1×27 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 6 6 6 6 6 6 6 6 6 5 6 6 5 6 5 6 5 5 6 5 5 6 5 5 6 6]
            MeanSequenceLength: 5.7037
               DeficitEditData: [10071×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

27 sequences from 3D structures
Using 10071 random sequences, 0 from an alignment, and 27 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 268, IL_66635.5  has acceptance rules AlignmentScore >= -24.7234, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  14.2234
TP   100.00%, TN    85.39%, min    85.39%,  27 3D sequences,     0 alignment sequences, 8900 random sequences, 1300 random matches,  5 NTs, cWW-L-cWW
Sensitivity 100.00%, Specificity  85.39%, Minimum  85.39% using method 11
Number of false positives with core edit > 0 is 1300
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11
Motif index 12
Motif index 13
Motif index 14
Motif index 15
Motif index 16
Motif index 17
Motif index 18
Motif index 19
Motif index 20
Motif index 21
Motif index 22
Motif index 23
Motif index 24
Motif index 25
Motif index 26
Motif index 27


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_66663.1'
                     Signature: {'cWW-L-tHS-tSW-tWH-cWH-cWW-L-cWW'  ''}
                         NumNT: 15
                  NumBasepairs: 8
                    Structured: 1
                     NumStacks: 12
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 9
                      NumFixed: 42
                      OwnScore: -10.0172
                   OwnSequence: {'GUCUGUGAUG*UGCAUGGC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 18
            MeanSequenceLength: 18
               DeficitEditData: [35×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 35 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  23.3195 because the cutoff seemed overly generous
Group 269, IL_66663.1  has acceptance rules AlignmentScore >= -30.0172, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  32.1175
TP   100.00%, TN    97.14%, min    97.14%,   1 3D sequences,     0 alignment sequences,   35 random sequences,    1 random matches, 15 NTs, cWW-L-tHS-tSW-tWH-cWH-cWW-L-cWW
Sensitivity 100.00%, Specificity  97.14%, Minimum  97.14% using method 8
Number of false positives with core edit > 0 is 1
1 * Deficit + 3 * Core Edit <= 22.1003
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_66798.2'
                     Signature: {'cWW-L-R-L-R-tHS-cWW'  ''}
                         NumNT: 10
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 2
                         NumBR: 1
                  NumInstances: 6
                      Truncate: 6
                      NumFixed: 30
                      OwnScore: [-4.8384 -4.8406 -4.8384 -5.6672 -5.6816 -7.0324]
                   OwnSequence: {'UUAAG*CGGAG'  'UUAAC*GGGAG'  'UUAAG*CGGAG'  'CUAAC*GGGAG'  'UUAAG*UGGAG'  'CGAAU*AGGAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10 10 10 10 10]
            MeanSequenceLength: 10
               DeficitEditData: [6780×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

6 sequences from 3D structures
Using 6780 random sequences, 0 from an alignment, and 6 from 3D structures
Group 270, IL_66798.2  has acceptance rules AlignmentScore >= -24.8384, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  19.2031
TP   100.00%, TN    96.00%, min    96.00%,   6 3D sequences,     0 alignment sequences, 6775 random sequences,  271 random matches, 10 NTs, cWW-L-R-L-R-tHS-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 271
1 * Deficit + 3 * Core Edit <= 14.3647
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_66997.2'
                     Signature: {'cWW-L-R-L-cWW-L'  ''}
                         NumNT: 8
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 6
                      NumFixed: 28
                      OwnScore: [-6.2688 -5.8873]
                   OwnSequence: {'GAAAU*ACAC'  'GGACC*GGC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 8]
            MeanSequenceLength: 8.5000
               DeficitEditData: [12987×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 12987 random sequences, 0 from an alignment, and 2 from 3D structures
Group 271, IL_66997.2  has acceptance rules AlignmentScore >= -25.8873, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.0849
TP   100.00%, TN    95.98%, min    95.98%,   2 3D sequences,     0 alignment sequences, 12977 random sequences,  522 random matches,  8 NTs, cWW-L-R-L-cWW-L
Sensitivity 100.00%, Specificity  95.98%, Minimum  95.98% using method 6
Number of false positives with core edit > 0 is 522
1 * Deficit + 3 * Core Edit <= 11.1976
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_67095.2'
                     Signature: {'cWW-tWW-cWW'  ''}
                         NumNT: 6
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 2
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 8
                      Truncate: 4
                      NumFixed: 14
                      OwnScore: [-4.1758 -4.2571 -4.1758 -4.3138 -4.2571 -4.3086 -4.1754 -9.2974]
                   OwnSequence: {'UAA*UCA'  'AAG*CCU'  'UAA*UCA'  'GAA*UCC'  'AAG*CCU'  'CAA*UCG'  'UAG*CCA'  'UAG*CAGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 6 6 6 6 6 7]
            MeanSequenceLength: 6.1250
               DeficitEditData: [7097×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

8 sequences from 3D structures
Using 7097 random sequences, 0 from an alignment, and 8 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 272, IL_67095.2  has acceptance rules AlignmentScore >= -24.1754, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.6754
TP   100.00%, TN    85.72%, min    85.72%,   8 3D sequences,     0 alignment sequences, 7005 random sequences, 1000 random matches,  6 NTs, cWW-tWW-cWW
Sensitivity 100.00%, Specificity  85.72%, Minimum  85.72% using method 11
Number of false positives with core edit > 0 is 1000
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_67623.1'
                     Signature: {'cWW-tSW-cSW-L-cSW-L-R-L-cWW-cWW'  ''}
                         NumNT: 14
                  NumBasepairs: 7
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 9
                      NumFixed: 38
                      OwnScore: -6.1591
                   OwnSequence: {'GGUUGCCU*AUAAGC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 14
            MeanSequenceLength: 14
               DeficitEditData: [186×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 186 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  20.1908 because the cutoff seemed overly generous
Group 273, IL_67623.1  has acceptance rules AlignmentScore >= -26.1591, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.1591
TP   100.00%, TN    96.24%, min    96.24%,   1 3D sequences,     0 alignment sequences,  186 random sequences,    7 random matches, 14 NTs, cWW-tSW-cSW-L-cSW-L-R-L-cWW-cWW
Sensitivity 100.00%, Specificity  96.24%, Minimum  96.24% using method 8
Number of false positives with core edit > 0 is 7
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_67767.4'
                     Signature: {'cWW-tWH-cWW-cSH-cWW'  ''}
                         NumNT: 9
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 7
                      Truncate: 6
                      NumFixed: 22
                      OwnScore: [-4.1338 -4.1338 -4.1338 -4.1338 -4.1338 -4.1338 -4.1338]
                   OwnSequence: {'CUAAG*UAUG'  'CUAAG*UAUG'  'CUAAG*UAUG'  'CUAAG*UAUG'  'CUAAG*UAUG'  'CUAAG*UAUG'  'CUAAG*UAUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 9 9 9 9 9]
            MeanSequenceLength: 9
               DeficitEditData: [3785×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

7 sequences from 3D structures
Using 3785 random sequences, 0 from an alignment, and 7 from 3D structures
Group 274, IL_67767.4  has acceptance rules AlignmentScore >= -24.1338, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  20.7051
TP   100.00%, TN    96.01%, min    96.01%,   7 3D sequences,     0 alignment sequences, 3784 random sequences,  151 random matches,  9 NTs, cWW-tWH-cWW-cSH-cWW
Sensitivity 100.00%, Specificity  96.01%, Minimum  96.01% using method 6
Number of false positives with core edit > 0 is 151
1 * Deficit + 3 * Core Edit <= 16.5713
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_67780.1'
                     Signature: {'cWW-cSH-L-R-L-L-R-L'  ''}
                         NumNT: 10
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 6
                      NumFixed: 38
                      OwnScore: -6.8769
                   OwnSequence: {'GUAGG*CACAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 10
            MeanSequenceLength: 10
               DeficitEditData: [8644×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 8644 random sequences, 0 from an alignment, and 1 from 3D structures
Group 275, IL_67780.1  has acceptance rules AlignmentScore >= -26.8769, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  21.5445
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 8644 random sequences,  346 random matches, 10 NTs, cWW-cSH-L-R-L-L-R-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 346
1 * Deficit + 3 * Core Edit <= 14.6676
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_68140.4'
                     Signature: {'cWW-cSH-cWW'  ''}
                         NumNT: 6
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 18
                      Truncate: 5
                      NumFixed: 22
                      OwnScore: [-3.8507 -3.8507 -4.3272 -4.3776 -4.3272 -4.3272 -3.4603 -3.4603 -3.2629 -3.2629 -3.2629 -3.2629 -3.2629 … ]
                   OwnSequence: {1×18 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 7]
            MeanSequenceLength: 6.0556
               DeficitEditData: [6485×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

18 sequences from 3D structures
Using 6485 random sequences, 0 from an alignment, and 18 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 276, IL_68140.4  has acceptance rules AlignmentScore >= -23.2629, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  12.7629
TP   100.00%, TN    93.11%, min    93.11%,  18 3D sequences,     0 alignment sequences, 6259 random sequences,  431 random matches,  6 NTs, cWW-cSH-cWW
Sensitivity 100.00%, Specificity  93.11%, Minimum  93.11% using method 11
Number of false positives with core edit > 0 is 431
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11
Motif index 12
Motif index 13
Motif index 14
Motif index 15
Motif index 16
Motif index 17
Motif index 18


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_68243.1'
                     Signature: {'cWW-L-cWW-cWW-R-L-tHS-cWW'  ''}
                         NumNT: 13
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 12
                        NumBPh: 2
                         NumBR: 3
                  NumInstances: 1
                      Truncate: 8
                      NumFixed: 34
                      OwnScore: -6.1763
                   OwnSequence: {'CGCUGAC*GGUGGAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 14
            MeanSequenceLength: 14
               DeficitEditData: [984×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 984 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  22.1572 because the cutoff seemed overly generous
Group 277, IL_68243.1  has acceptance rules AlignmentScore >= -26.1763, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.1763
TP   100.00%, TN    97.66%, min    97.66%,   1 3D sequences,     0 alignment sequences,  984 random sequences,   23 random matches, 13 NTs, cWW-L-cWW-cWW-R-L-tHS-cWW
Sensitivity 100.00%, Specificity  97.66%, Minimum  97.66% using method 8
Number of false positives with core edit > 0 is 23
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_68405.1'
                     Signature: {'cWW-cSS-L-tWH-tHW-cWW-cWW'  ''}
                         NumNT: 11
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 7
                      NumFixed: 22
                      OwnScore: -7.7027
                   OwnSequence: {'CAACAGC*GACAUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 13
            MeanSequenceLength: 13
               DeficitEditData: [3531×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 3531 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  20.4984 because the cutoff seemed overly generous
Group 278, IL_68405.1  has acceptance rules AlignmentScore >= -27.7027, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  27.7027
TP   100.00%, TN    96.60%, min    96.60%,   1 3D sequences,     0 alignment sequences, 3531 random sequences,  120 random matches, 11 NTs, cWW-cSS-L-tWH-tHW-cWW-cWW
Sensitivity 100.00%, Specificity  96.60%, Minimum  96.60% using method 8
Number of false positives with core edit > 0 is 120
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_68574.4'
                     Signature: {'cWW-tHH-tHS-cWW'  ''}
                         NumNT: 8
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 2
                         NumBR: 1
                  NumInstances: 3
                      Truncate: 5
                      NumFixed: 16
                      OwnScore: [-5.9744 -5.7960 -8.4575]
                   OwnSequence: {'UAAG*UGAUG'  'UAAG*CGAUG'  'CACC*GCAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 9]
            MeanSequenceLength: 9
               DeficitEditData: [8501×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 8501 random sequences, 0 from an alignment, and 3 from 3D structures
Group 279, IL_68574.4  has acceptance rules AlignmentScore >= -25.7960, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  18.3057
TP   100.00%, TN    96.00%, min    96.00%,   3 3D sequences,     0 alignment sequences, 8498 random sequences,  340 random matches,  8 NTs, cWW-tHH-tHS-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 340
1 * Deficit + 3 * Core Edit <= 12.5097
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_68909.1'
                     Signature: {'cWW-L-R-L-R-L-cWW'  ''}
                         NumNT: 9
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 6
                      Truncate: 6
                      NumFixed: 20
                      OwnScore: [-9.9132 -9.6530 -8.7029 -10.3558 -12.6506 -13.2302]
                   OwnSequence: {'GGAGG*CGCC'  'GAUUC*GGCU'  'GUAUC*GUUC'  'GGCCC*GGGC'  'CAUGG*UAUAG'  'GAUCAC*GGAAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 9 9 10 11]
            MeanSequenceLength: 9.5000
               DeficitEditData: [15286×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

6 sequences from 3D structures
Using 15286 random sequences, 0 from an alignment, and 6 from 3D structures
Group 280, IL_68909.1  has acceptance rules AlignmentScore >= -28.7029, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  19.0104
TP   100.00%, TN    96.00%, min    96.00%,   6 3D sequences,     0 alignment sequences, 15283 random sequences,  611 random matches,  9 NTs, cWW-L-R-L-R-L-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 611
1 * Deficit + 3 * Core Edit <= 10.3075
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_69000.1'
                     Signature: {'cWW-L-cWW-L-cWW-L'  ''}
                         NumNT: 9
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 7
                      NumFixed: 26
                      OwnScore: [-5.3967 -5.3967]
                   OwnSequence: {'GGGCGC*GAC'  'GGGCGC*GAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9]
            MeanSequenceLength: 9
               DeficitEditData: [12662×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 12662 random sequences, 0 from an alignment, and 2 from 3D structures
Group 281, IL_69000.1  has acceptance rules AlignmentScore >= -25.3967, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  21.1359
TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 12661 random sequences,  507 random matches,  9 NTs, cWW-L-cWW-L-cWW-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 507
1 * Deficit + 3 * Core Edit <= 15.7392
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_69145.3'
                     Signature: {'cWW-L-cWW-L-R-L-R-R'  ''}
                         NumNT: 10
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 4
                      Truncate: 7
                      NumFixed: 36
                      OwnScore: [-4.2307 -4.2307 -5.9253 -4.2307]
                   OwnSequence: {'UCCUGC*GAAA'  'UCCUGC*GAAA'  'UCCAGC*GGAA'  'UCCUGC*GAAA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10 10 10]
            MeanSequenceLength: 10
               DeficitEditData: [10330×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 10330 random sequences, 0 from an alignment, and 4 from 3D structures
Group 282, IL_69145.3  has acceptance rules AlignmentScore >= -24.2307, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  22.2626
TP   100.00%, TN    96.00%, min    96.00%,   4 3D sequences,     0 alignment sequences, 10330 random sequences,  413 random matches, 10 NTs, cWW-L-cWW-L-R-L-R-R
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 413
1 * Deficit + 3 * Core Edit <= 18.0319
Motif index 1
Motif index 2
Motif index 3
Motif index 4


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_69229.3'
                     Signature: {'cWW-L-tSH-L-tHS-cWW-cWW'  ''}
                         NumNT: 12
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 11
                        NumBPh: 0
                         NumBR: 4
                  NumInstances: 8
                      Truncate: 8
                      NumFixed: 30
                      OwnScore: [-7.8603 -8.1011 -8.1011 -7.8603 -7.8603 -10.0076 -12.8561 -11.2652]
                   OwnSequence: {1×8 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [13 13 13 13 13 13 14 13]
            MeanSequenceLength: 13.1250
               DeficitEditData: [4247×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

8 sequences from 3D structures
Using 4247 random sequences, 0 from an alignment, and 8 from 3D structures
Group 283, IL_69229.3  has acceptance rules AlignmentScore >= -27.8603, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  27.6678
TP   100.00%, TN    96.00%, min    96.00%,   8 3D sequences,     0 alignment sequences, 4247 random sequences,  170 random matches, 12 NTs, cWW-L-tSH-L-tHS-cWW-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 170
1 * Deficit + 3 * Core Edit <= 19.8075
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_69271.3'
                     Signature: {'cWW-cWW-L-R-L-cWW-L-L-R'  ''}
                         NumNT: 12
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 9
                      NumFixed: 38
                      OwnScore: [-9.4563 -7.9158]
                   OwnSequence: {'CUGACGGAACG*CAUG'  'CUGACGGAAG*CAUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [15 14]
            MeanSequenceLength: 14.5000
               DeficitEditData: [2369×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 2369 random sequences, 0 from an alignment, and 2 from 3D structures
Decreased cutoff from  21.8454 because the cutoff seemed overly generous
Group 284, IL_69271.3  has acceptance rules AlignmentScore >= -27.9158, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  27.9158
TP   100.00%, TN    97.64%, min    97.64%,   2 3D sequences,     0 alignment sequences, 2369 random sequences,   56 random matches, 12 NTs, cWW-cWW-L-R-L-cWW-L-L-R
Sensitivity 100.00%, Specificity  97.64%, Minimum  97.64% using method 8
Number of false positives with core edit > 0 is 56
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_69440.3'
                     Signature: {'cWW-L-R-cSH-cWW'  ''}
                         NumNT: 8
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 3
                      Truncate: 6
                      NumFixed: 26
                      OwnScore: [-5.4385 -4.9277 -4.9277]
                   OwnSequence: {'CAAAA*UAG'  'CGAAA*UAG'  'CGAAA*UAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8 8]
            MeanSequenceLength: 8
               DeficitEditData: [12075×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 12075 random sequences, 0 from an alignment, and 3 from 3D structures
Group 285, IL_69440.3  has acceptance rules AlignmentScore >= -24.9277, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.1985
TP   100.00%, TN    95.94%, min    95.94%,   3 3D sequences,     0 alignment sequences, 12042 random sequences,  489 random matches,  8 NTs, cWW-L-R-cSH-cWW
Sensitivity 100.00%, Specificity  95.94%, Minimum  95.94% using method 6
Number of false positives with core edit > 0 is 489
1 * Deficit + 3 * Core Edit <= 11.2708
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_69543.3'
                     Signature: {'cWW-tSH-L-R-tSS-tHS-L-R-cWW'  ''}
                         NumNT: 12
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 1
                         NumBR: 4
                  NumInstances: 3
                      Truncate: 7
                      NumFixed: 32
                      OwnScore: [-8.3002 -8.5275 -12.2321]
                   OwnSequence: {'CGGAAUU*GGAGAUG'  'UGGAAUU*GGAGAUG'  'CAGAGAA*UGUGAGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [14 14 14]
            MeanSequenceLength: 14
               DeficitEditData: [2624×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 2624 random sequences, 0 from an alignment, and 3 from 3D structures
Group 286, IL_69543.3  has acceptance rules AlignmentScore >= -28.3002, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  27.7174
TP   100.00%, TN    96.00%, min    96.00%,   3 3D sequences,     0 alignment sequences, 2624 random sequences,  105 random matches, 12 NTs, cWW-tSH-L-R-tSS-tHS-L-R-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 105
1 * Deficit + 3 * Core Edit <= 19.4172
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_69986.1'
                     Signature: {'cWW-cHW-L-R-L-R-cWH-cWW'  ''}
                         NumNT: 12
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 12
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 7
                      NumFixed: 20
                      OwnScore: -6.6940
                   OwnSequence: {'UGAUGA*UGAUGA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 12
            MeanSequenceLength: 12
               DeficitEditData: [2090×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 2090 random sequences, 0 from an alignment, and 1 from 3D structures
Group 287, IL_69986.1  has acceptance rules AlignmentScore >= -26.6940, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.3373
TP   100.00%, TN    95.98%, min    95.98%,   1 3D sequences,     0 alignment sequences, 2090 random sequences,   84 random matches, 12 NTs, cWW-cHW-L-R-L-R-cWH-cWW
Sensitivity 100.00%, Specificity  95.98%, Minimum  95.98% using method 6
Number of false positives with core edit > 0 is 84
1 * Deficit + 3 * Core Edit <= 19.6433
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_70096.1'
                     Signature: {'cWW-L-cWW-cWW'  ''}
                         NumNT: 7
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 5
                      NumFixed: 18
                      OwnScore: -6.8273
                   OwnSequence: {'UUUG*CUUAUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 10
            MeanSequenceLength: 10
               DeficitEditData: [9519×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 9519 random sequences, 0 from an alignment, and 1 from 3D structures
Group 288, IL_70096.1  has acceptance rules AlignmentScore >= -26.8273, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.2076
TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences, 9519 random sequences,  382 random matches,  7 NTs, cWW-L-cWW-cWW
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 382
1 * Deficit + 3 * Core Edit <= 17.3802
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_70335.1'
                     Signature: {'cWW-L-R-L-cWW'  ''}
                         NumNT: 7
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 1
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 5
                      NumFixed: 24
                      OwnScore: [-5.4816 -5.4816]
                   OwnSequence: {'UCUAU*ACGA'  'UCUAU*ACGA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9]
            MeanSequenceLength: 9
               DeficitEditData: [14671×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 14671 random sequences, 0 from an alignment, and 2 from 3D structures
Group 289, IL_70335.1  has acceptance rules AlignmentScore >= -25.4816, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  20.3302
TP   100.00%, TN    95.99%, min    95.99%,   2 3D sequences,     0 alignment sequences, 14671 random sequences,  588 random matches,  7 NTs, cWW-L-R-L-cWW
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 588
1 * Deficit + 3 * Core Edit <= 14.8485
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_70376.1'
                     Signature: {'cWW-L-cWW-L'  ''}
                         NumNT: 6
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 5
                      NumFixed: 20
                      OwnScore: -5.1466
                   OwnSequence: {'UGUGUA*UG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 8
            MeanSequenceLength: 8
               DeficitEditData: [13508×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 13508 random sequences, 0 from an alignment, and 1 from 3D structures
Group 290, IL_70376.1  has acceptance rules AlignmentScore >= -25.1466, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.7532
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 13505 random sequences,  540 random matches,  6 NTs, cWW-L-cWW-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 540
1 * Deficit + 3 * Core Edit <= 12.6066
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_70411.2'
                     Signature: {'cWW-tSH-L-tHH-L-cWW'  ''}
                         NumNT: 10
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 1
                         NumBR: 3
                  NumInstances: 7
                      Truncate: 7
                      NumFixed: 24
                      OwnScore: [-6.4620 -6.4620 -8.4578 -8.6368 -8.0578 -5.4889 -5.4889]
                   OwnSequence: {1×7 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11 11 11 11 11 11]
            MeanSequenceLength: 11
               DeficitEditData: [5146×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

7 sequences from 3D structures
Using 5146 random sequences, 0 from an alignment, and 7 from 3D structures
Group 291, IL_70411.2  has acceptance rules AlignmentScore >= -25.4889, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  22.3328
TP   100.00%, TN    96.00%, min    96.00%,   7 3D sequences,     0 alignment sequences, 5145 random sequences,  206 random matches, 10 NTs, cWW-tSH-L-tHH-L-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 206
1 * Deficit + 3 * Core Edit <= 16.8439
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_70627.3'
                     Signature: {'cWW-L-R-tHW-cWW'  ''}
                         NumNT: 10
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 2
                         NumBR: 0
                  NumInstances: 3
                      Truncate: 7
                      NumFixed: 30
                      OwnScore: [-6.8722 -6.7308 -9.3553]
                   OwnSequence: {'GGAGUC*GUGAC'  'AGAGCC*GUAAU'  'CGAAAUG*CUAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11 12]
            MeanSequenceLength: 11.3333
               DeficitEditData: [13307×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 13307 random sequences, 0 from an alignment, and 3 from 3D structures
Group 292, IL_70627.3  has acceptance rules AlignmentScore >= -26.7308, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  23.0696
TP   100.00%, TN    96.00%, min    96.00%,   3 3D sequences,     0 alignment sequences, 13306 random sequences,  532 random matches, 10 NTs, cWW-L-R-tHW-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 532
1 * Deficit + 3 * Core Edit <= 16.3388
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_70670.1'
                     Signature: {'cWW-R-L-R-L-R-L-R-L-R-L-R-tWH-L-R-L'  ''}
                         NumNT: 18
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 18
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 10
                      NumFixed: 52
                      OwnScore: -12.3312
                   OwnSequence: {'GAAGAGUAU*AGAAGGCAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 18
            MeanSequenceLength: 18
               DeficitEditData: [185×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 185 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  23.0177 because the cutoff seemed overly generous
Group 293, IL_70670.1  has acceptance rules AlignmentScore >= -32.3312, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  34.4384
TP   100.00%, TN    97.84%, min    97.84%,   1 3D sequences,     0 alignment sequences,  185 random sequences,    4 random matches, 18 NTs, cWW-R-L-R-L-R-L-R-L-R-L-R-tWH-L-R-L
Sensitivity 100.00%, Specificity  97.84%, Minimum  97.84% using method 8
Number of false positives with core edit > 0 is 4
1 * Deficit + 3 * Core Edit <= 22.1071
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_70801.1'
                     Signature: {'cWW-cWW-L-R-tWW-L-R-L-cWW'  ''}
                         NumNT: 13
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 12
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 8
                      NumFixed: 30
                      OwnScore: -6.8858
                   OwnSequence: {'CAUUGAC*GAAGGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 13
            MeanSequenceLength: 13
               DeficitEditData: [2301×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 2301 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  21.0717 because the cutoff seemed overly generous
Group 294, IL_70801.1  has acceptance rules AlignmentScore >= -26.8858, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.8858
TP   100.00%, TN    97.48%, min    97.48%,   1 3D sequences,     0 alignment sequences, 2301 random sequences,   58 random matches, 13 NTs, cWW-cWW-L-R-tWW-L-R-L-cWW
Sensitivity 100.00%, Specificity  97.48%, Minimum  97.48% using method 8
Number of false positives with core edit > 0 is 58
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_70923.9'
                     Signature: {'cWW-tSS-tSH-L-tHS-tHS-cWW'  ''}
                         NumNT: 12
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 12
                        NumBPh: 2
                         NumBR: 5
                  NumInstances: 27
                      Truncate: 8
                      NumFixed: 28
                      OwnScore: [-5.4957 -5.4957 -5.4957 -5.4957 -10.4335 -9.7798 -5.4957 -6.1767 -5.4957 -5.4957 -5.4957 -13.2210 … ]
                   OwnSequence: {1×27 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13]
            MeanSequenceLength: 13
               DeficitEditData: [2249×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

27 sequences from 3D structures
Using 2249 random sequences, 0 from an alignment, and 27 from 3D structures
Group 295, IL_70923.9  has acceptance rules AlignmentScore >= -25.4957, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  23.7118
TP   100.00%, TN    96.00%, min    96.00%,  27 3D sequences,     0 alignment sequences, 2249 random sequences,   90 random matches, 12 NTs, cWW-tSS-tSH-L-tHS-tHS-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 90
1 * Deficit + 3 * Core Edit <= 18.2161
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11
Motif index 12
Motif index 13
Motif index 14
Motif index 15
Motif index 16
Motif index 17
Motif index 18
Motif index 19
Motif index 20
Motif index 21
Motif index 22
Motif index 23
Motif index 24
Motif index 25
Motif index 26
Motif index 27


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_71294.3'
                     Signature: {'cWW-L-R-L-R-L-R-L-R-cWW'  ''}
                         NumNT: 12
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 13
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 7
                      NumFixed: 26
                      OwnScore: [-7.9291 -11.5269]
                   OwnSequence: {'CCAGGU*GAGCAG'  'AGAGAC*GUCAAU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [12 12]
            MeanSequenceLength: 12
               DeficitEditData: [6203×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 6203 random sequences, 0 from an alignment, and 2 from 3D structures
Group 296, IL_71294.3  has acceptance rules AlignmentScore >= -27.9291, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.8607
TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 6203 random sequences,  248 random matches, 12 NTs, cWW-L-R-L-R-L-R-L-R-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 248
1 * Deficit + 3 * Core Edit <= 17.9316
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_71598.1'
                     Signature: {'cWW-tSH-L-cWW-L'  ''}
                         NumNT: 8
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 6
                      NumFixed: 22
                      OwnScore: -6.2181
                   OwnSequence: {'GGAAA*UAAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 9
            MeanSequenceLength: 9
               DeficitEditData: [13611×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 13611 random sequences, 0 from an alignment, and 1 from 3D structures
Group 297, IL_71598.1  has acceptance rules AlignmentScore >= -26.2181, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  18.2011
TP   100.00%, TN    95.98%, min    95.98%,   1 3D sequences,     0 alignment sequences, 13603 random sequences,  547 random matches,  8 NTs, cWW-tSH-L-cWW-L
Sensitivity 100.00%, Specificity  95.98%, Minimum  95.98% using method 6
Number of false positives with core edit > 0 is 547
1 * Deficit + 3 * Core Edit <= 11.9830
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_73002.1'
                     Signature: {'cWW-L-R-L-R-L-R-L-R-L-cWW-L-L-R'  ''}
                         NumNT: 16
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 11
                      NumFixed: 60
                      OwnScore: -12.2297
                   OwnSequence: {'UGGAUUUCCAA*UUGGCCG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 18
            MeanSequenceLength: 18
               DeficitEditData: [20×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 20 random sequences, 0 from an alignment, and 1 from 3D structures
Group 298, IL_73002.1  has acceptance rules AlignmentScore >= -32.2297, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  37.2297
TP   100.00%, TN    85.00%, min    85.00%,   1 3D sequences,     0 alignment sequences,   20 random sequences,    3 random matches, 16 NTs, cWW-L-R-L-R-L-R-L-R-L-cWW-L-L-R
Sensitivity 100.00%, Specificity  85.00%, Minimum  85.00% using method 1
Number of false positives with core edit > 0 is 3
1 * Deficit + 3 * Core Edit <= 25.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_73355.1'
                     Signature: {'cWW-L-cWW-L'  ''}
                         NumNT: 6
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 5
                      NumFixed: 20
                      OwnScore: [-3.9345 -3.9345]
                   OwnSequence: {'CAAC*GG'  'CAAC*GG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6]
            MeanSequenceLength: 6
               DeficitEditData: [8964×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 8964 random sequences, 0 from an alignment, and 2 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 299, IL_73355.1  has acceptance rules AlignmentScore >= -23.9345, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.4345
TP   100.00%, TN    85.96%, min    85.96%,   2 3D sequences,     0 alignment sequences, 8867 random sequences, 1245 random matches,  6 NTs, cWW-L-cWW-L
Sensitivity 100.00%, Specificity  85.96%, Minimum  85.96% using method 11
Number of false positives with core edit > 0 is 1245
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_73452.2'
                     Signature: {'cWW-L-cWW'  ''}
                         NumNT: 5
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 3
                      Truncate: 4
                      NumFixed: 16
                      OwnScore: [-5.5729 -5.7716 -6.8814]
                   OwnSequence: {'CUAG*CG'  'GUC*GC'  'GAAUG*CC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 5 7]
            MeanSequenceLength: 6
               DeficitEditData: [12067×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 12067 random sequences, 0 from an alignment, and 3 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 300, IL_73452.2  has acceptance rules AlignmentScore >= -25.5729, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.0729
TP   100.00%, TN    82.61%, min    82.61%,   3 3D sequences,     0 alignment sequences, 11695 random sequences, 2034 random matches,  5 NTs, cWW-L-cWW
Sensitivity 100.00%, Specificity  82.61%, Minimum  82.61% using method 11
Number of false positives with core edit > 0 is 2034
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_73700.1'
                     Signature: {'cWW-L-R-L-cWW-L-cWW-tHS-cWW'  ''}
                         NumNT: 13
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 11
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 8
                      NumFixed: 38
                      OwnScore: -9.0598
                   OwnSequence: {'CGCUUUUUGG*CGACAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 16
            MeanSequenceLength: 16
               DeficitEditData: [76×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 76 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  21.2004 because the cutoff seemed overly generous
Group 301, IL_73700.1  has acceptance rules AlignmentScore >= -29.0598, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  30.0199
TP   100.00%, TN    97.37%, min    97.37%,   1 3D sequences,     0 alignment sequences,   76 random sequences,    2 random matches, 13 NTs, cWW-L-R-L-cWW-L-cWW-tHS-cWW
Sensitivity 100.00%, Specificity  97.37%, Minimum  97.37% using method 8
Number of false positives with core edit > 0 is 2
1 * Deficit + 3 * Core Edit <= 20.9601
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_73759.1'
                     Signature: {'cWW-cSH-tHS-cWH-cHW-cWW'  ''}
                         NumNT: 9
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 6
                      NumFixed: 24
                      OwnScore: -4.8710
                   OwnSequence: {'GAGGGG*CGGUC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 11
            MeanSequenceLength: 11
               DeficitEditData: [4790×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 4790 random sequences, 0 from an alignment, and 1 from 3D structures
Group 302, IL_73759.1  has acceptance rules AlignmentScore >= -24.8710, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.3835
TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences, 4790 random sequences,  192 random matches,  9 NTs, cWW-cSH-tHS-cWH-cHW-cWW
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 192
1 * Deficit + 3 * Core Edit <= 19.5125
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_73789.1'
                     Signature: {'cWW-L-R-L-cWW-L'  ''}
                         NumNT: 8
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 2
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 6
                      NumFixed: 22
                      OwnScore: [-4.3606 -4.3606]
                   OwnSequence: {'CGAUUC*GGG'  'CGAUUC*GGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9]
            MeanSequenceLength: 9
               DeficitEditData: [11913×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 11913 random sequences, 0 from an alignment, and 2 from 3D structures
Group 303, IL_73789.1  has acceptance rules AlignmentScore >= -24.3606, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  20.1835
TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 11911 random sequences,  477 random matches,  8 NTs, cWW-L-R-L-cWW-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 477
1 * Deficit + 3 * Core Edit <= 15.8228
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_74051.1'
                     Signature: {'cWW-tSS-tSH-L-tHS-cWW-L'  ''}
                         NumNT: 11
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 0
                         NumBR: 5
                  NumInstances: 3
                      Truncate: 8
                      NumFixed: 30
                      OwnScore: [-4.7926 -4.7926 -4.7926]
                   OwnSequence: {'CGGUGAAG*CGAG'  'CGGUGAAG*CGAG'  'CGGUGAAG*CGAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [12 12 12]
            MeanSequenceLength: 12
               DeficitEditData: [3022×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 3022 random sequences, 0 from an alignment, and 3 from 3D structures
Group 304, IL_74051.1  has acceptance rules AlignmentScore >= -24.7926, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.4275
TP   100.00%, TN    96.00%, min    96.00%,   3 3D sequences,     0 alignment sequences, 3022 random sequences,  121 random matches, 11 NTs, cWW-tSS-tSH-L-tHS-cWW-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 121
1 * Deficit + 3 * Core Edit <= 19.6349
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_74184.1'
                     Signature: {'cWW-L-tHS-L-cWW-L-L-L'  ''}
                         NumNT: 11
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 9
                      NumFixed: 34
                      OwnScore: -8.2609
                   OwnSequence: {'CGGGAUGUG*CGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 12
            MeanSequenceLength: 12
               DeficitEditData: [5852×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 5852 random sequences, 0 from an alignment, and 1 from 3D structures
Group 305, IL_74184.1  has acceptance rules AlignmentScore >= -28.2609, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.6986
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 5852 random sequences,  234 random matches, 11 NTs, cWW-L-tHS-L-cWW-L-L-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 234
1 * Deficit + 3 * Core Edit <= 18.4377
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_74367.1'
                     Signature: {'cWW-L-R-L-R-L-R-cWW'  ''}
                         NumNT: 10
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 6
                      NumFixed: 30
                      OwnScore: [-7.1614 -5.2470]
                   OwnSequence: {'GUUUG*CAUAC'  'GUUUG*CGUAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10]
            MeanSequenceLength: 10
               DeficitEditData: [8372×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 8372 random sequences, 0 from an alignment, and 2 from 3D structures
Group 306, IL_74367.1  has acceptance rules AlignmentScore >= -25.2470, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  21.3517
TP   100.00%, TN    95.97%, min    95.97%,   2 3D sequences,     0 alignment sequences, 8372 random sequences,  337 random matches, 10 NTs, cWW-L-R-L-R-L-R-cWW
Sensitivity 100.00%, Specificity  95.97%, Minimum  95.97% using method 6
Number of false positives with core edit > 0 is 337
1 * Deficit + 3 * Core Edit <= 16.1047
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_74746.1'
                     Signature: {'cWW-L-R-L-R-L-R-L-R-L-R-L-R-cWW'  ''}
                         NumNT: 16
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 12
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 9
                      NumFixed: 54
                      OwnScore: [-14.5056 -14.9033]
                   OwnSequence: {'GAAACCGCG*UUCGCUCC'  'CUUGAGUG*UAAUUAUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [17 16]
            MeanSequenceLength: 16.5000
               DeficitEditData: [551×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 551 random sequences, 0 from an alignment, and 2 from 3D structures
Decreased cutoff from  20.0903 because the cutoff seemed overly generous
Group 307, IL_74746.1  has acceptance rules AlignmentScore >= -34.5056, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  34.5056
TP   100.00%, TN    96.01%, min    96.01%,   2 3D sequences,     0 alignment sequences,  551 random sequences,   22 random matches, 16 NTs, cWW-L-R-L-R-L-R-L-R-L-R-L-R-cWW
Sensitivity 100.00%, Specificity  96.01%, Minimum  96.01% using method 8
Number of false positives with core edit > 0 is 22
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_74957.1'
                     Signature: {'cWW-L-cHW-L-cWW-L'  ''}
                         NumNT: 9
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 7
                      NumFixed: 26
                      OwnScore: -7.6461
                   OwnSequence: {'UAAUAAGC*GUA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 11
            MeanSequenceLength: 11
               DeficitEditData: [10705×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 10705 random sequences, 0 from an alignment, and 1 from 3D structures
Group 308, IL_74957.1  has acceptance rules AlignmentScore >= -27.6461, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.4315
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 10705 random sequences,  428 random matches,  9 NTs, cWW-L-cHW-L-cWW-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 428
1 * Deficit + 3 * Core Edit <= 16.7854
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_75283.2'
                     Signature: {'cWW-tSS-L-R-L-tHS-L-cWW-L-tWH-tWH-L-L-R'  ''}
                         NumNT: 18
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 16
                        NumBPh: 4
                         NumBR: 2
                  NumInstances: 3
                      Truncate: 15
                      NumFixed: 40
                      OwnScore: [-6.7178 -8.2502 -6.7178]
                   OwnSequence: {'CGCCGGUGAAAUAC*GGAG'  'CAACAGUGAAAUAC*GGAG'  'CGCCGGUGAAAUAC*GGAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [18 18 18]
            MeanSequenceLength: 18
               DeficitEditData: [18×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 18 random sequences, 0 from an alignment, and 3 from 3D structures
Group 309, IL_75283.2  has acceptance rules AlignmentScore >= -26.7178, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  31.7178
TP   100.00%, TN    83.33%, min    83.33%,   3 3D sequences,     0 alignment sequences,   18 random sequences,    3 random matches, 18 NTs, cWW-tSS-L-R-L-tHS-L-cWW-L-tWH-tWH-L-L-R
Sensitivity 100.00%, Specificity  83.33%, Minimum  83.33% using method 1
Number of false positives with core edit > 0 is 3
1 * Deficit + 3 * Core Edit <= 25.0000
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_75294.1'
                     Signature: {'cWW-L-R-L-R-L-cWW'  ''}
                         NumNT: 9
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 6
                      NumFixed: 26
                      OwnScore: [-9.0311 -7.9162]
                   OwnSequence: {'CCGAC*GGGG'  'GCGAGG*CAAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 10]
            MeanSequenceLength: 9.5000
               DeficitEditData: [16501×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 16501 random sequences, 0 from an alignment, and 2 from 3D structures
Group 310, IL_75294.1  has acceptance rules AlignmentScore >= -27.9162, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  20.6075
TP   100.00%, TN    95.99%, min    95.99%,   2 3D sequences,     0 alignment sequences, 16500 random sequences,  661 random matches,  9 NTs, cWW-L-R-L-R-L-cWW
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 661
1 * Deficit + 3 * Core Edit <= 12.6912
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_76308.6'
                     Signature: {'cWW-tSH-tHW-tHS-cWW-cWW'  ''}
                         NumNT: 12
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 13
                        NumBPh: 2
                         NumBR: 0
                  NumInstances: 5
                      Truncate: 7
                      NumFixed: 20
                      OwnScore: [-7.4493 -8.1049 -7.4493 -12.0486 -14.9368]
                   OwnSequence: {'UCAGGU*AAGCAG'  'CCAGGU*GAGCAG'  'UCAGGU*AAGCAG'  'CUACCC*GAACAG'  'GGCCAG*CUCAAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [12 12 12 12 12]
            MeanSequenceLength: 12
               DeficitEditData: [3079×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

5 sequences from 3D structures
Using 3079 random sequences, 0 from an alignment, and 5 from 3D structures
Group 311, IL_76308.6  has acceptance rules AlignmentScore >= -27.4493, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.2664
TP   100.00%, TN    96.01%, min    96.01%,   5 3D sequences,     0 alignment sequences, 3079 random sequences,  123 random matches, 12 NTs, cWW-tSH-tHW-tHS-cWW-cWW
Sensitivity 100.00%, Specificity  96.01%, Minimum  96.01% using method 6
Number of false positives with core edit > 0 is 123
1 * Deficit + 3 * Core Edit <= 17.8171
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_76319.5'
                     Signature: {'cWW-L-R-L-cWW'  ''}
                         NumNT: 7
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 3
                      Truncate: 5
                      NumFixed: 18
                      OwnScore: [-4.7963 -4.7963 -4.7963]
                   OwnSequence: {'UGCAU*AUG'  'UGCAU*AUG'  'UGCAU*AUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8 8]
            MeanSequenceLength: 8
               DeficitEditData: [11384×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 11384 random sequences, 0 from an alignment, and 3 from 3D structures
Group 312, IL_76319.5  has acceptance rules AlignmentScore >= -24.7963, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.9108
TP   100.00%, TN    96.00%, min    96.00%,   3 3D sequences,     0 alignment sequences, 11383 random sequences,  455 random matches,  7 NTs, cWW-L-R-L-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 455
1 * Deficit + 3 * Core Edit <= 13.1145
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_76460.1'
                     Signature: {'cWW-cWW-L-tHS-L-R-L-cWW-L-L-R-L-L-R-L-R-L-R'  ''}
                         NumNT: 22
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 20
                        NumBPh: 1
                         NumBR: 3
                  NumInstances: 1
                      Truncate: 18
                      NumFixed: 56
                      OwnScore: -12.3350
                   OwnSequence: {'CUCAGACCCGAAGCGUG*CGGUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 22
            MeanSequenceLength: 22
               DeficitEditData: [0×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 0 random sequences, 0 from an alignment, and 1 from 3D structures
No random sequence matches, so essentially no model-specific cutoff imposed
Decreased cutoff to  25.0000 so that it is possible to reject matches
Group 313, IL_76460.1  has acceptance rules AlignmentScore >= -32.3350, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  37.3350
TP   100.00%, TN      NaN%, min   100.00%,   1 3D sequences,     0 alignment sequences,    0 random sequences,    0 random matches, 22 NTs, cWW-cWW-L-tHS-L-R-L-cWW-L-L-R-L-L-R-L-R-L-R
Sensitivity 100.00%, Specificity    NaN%, Minimum 100.00% using method 12
Number of false positives with core edit > 0 is 0
1 * Deficit + 3 * Core Edit <= 25.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_76709.2'
                     Signature: {'cWW-L-cWW-L'  ''}
                         NumNT: 6
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 4
                      Truncate: 5
                      NumFixed: 20
                      OwnScore: [-4.9804 -4.8803 -4.8765 -4.4358]
                   OwnSequence: {'GAAG*CC'  'GACC*GC'  'UAUC*GG'  'AAUC*GU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 6 6]
            MeanSequenceLength: 6
               DeficitEditData: [7991×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 7991 random sequences, 0 from an alignment, and 4 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 314, IL_76709.2  has acceptance rules AlignmentScore >= -24.4358, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.9358
TP   100.00%, TN    85.61%, min    85.61%,   4 3D sequences,     0 alignment sequences, 7816 random sequences, 1125 random matches,  6 NTs, cWW-L-cWW-L
Sensitivity 100.00%, Specificity  85.61%, Minimum  85.61% using method 11
Number of false positives with core edit > 0 is 1125
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_76758.2'
                     Signature: {'cWW-L-R-L-cWW-L-L'  ''}
                         NumNT: 9
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 3
                         NumBR: 0
                  NumInstances: 7
                      Truncate: 7
                      NumFixed: 32
                      OwnScore: [-5.9639 -4.6646 -5.4531 -5.9996 -6.7524 -5.3404 -5.3404]
                   OwnSequence: {'ACUAGG*CUGU'  'ACUCGG*CUGU'  'ACUCUG*CUGU'  'AUUCGG*CUGU'  'ACUUUG*CUGU'  'AGUCGG*CUGU'  'AGUCGG*CUGU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10 10 10 10 10 10]
            MeanSequenceLength: 10
               DeficitEditData: [8523×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

7 sequences from 3D structures
Using 8523 random sequences, 0 from an alignment, and 7 from 3D structures
Group 315, IL_76758.2  has acceptance rules AlignmentScore >= -24.6646, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  22.2891
TP   100.00%, TN    96.00%, min    96.00%,   7 3D sequences,     0 alignment sequences, 8523 random sequences,  341 random matches,  9 NTs, cWW-L-R-L-cWW-L-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 341
1 * Deficit + 3 * Core Edit <= 17.6245
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_77045.1'
                     Signature: {'cWW-L-tSW-L-tHW-cWW-L'  ''}
                         NumNT: 11
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 8
                      NumFixed: 34
                      OwnScore: -7.9163
                   OwnSequence: {'AUAUGAGG*UAAAU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 13
            MeanSequenceLength: 13
               DeficitEditData: [3970×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 3970 random sequences, 0 from an alignment, and 1 from 3D structures
Group 316, IL_77045.1  has acceptance rules AlignmentScore >= -27.9163, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  27.5329
TP   100.00%, TN    95.97%, min    95.97%,   1 3D sequences,     0 alignment sequences, 3970 random sequences,  160 random matches, 11 NTs, cWW-L-tSW-L-tHW-cWW-L
Sensitivity 100.00%, Specificity  95.97%, Minimum  95.97% using method 6
Number of false positives with core edit > 0 is 160
1 * Deficit + 3 * Core Edit <= 19.6166
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_77278.1'
                     Signature: {'cWW-tWW-L-tWW-cWW-L'  ''}
                         NumNT: 10
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 2
                  NumInstances: 2
                      Truncate: 7
                      NumFixed: 24
                      OwnScore: [-7.5339 -7.5339]
                   OwnSequence: {'CUCAUCAG*CUCAAG'  'CUCAUCAG*CUCAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [14 14]
            MeanSequenceLength: 14
               DeficitEditData: [1850×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 1850 random sequences, 0 from an alignment, and 2 from 3D structures
Decreased cutoff from  23.1804 because the cutoff seemed overly generous
Group 317, IL_77278.1  has acceptance rules AlignmentScore >= -27.5339, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  29.0775
TP   100.00%, TN    98.00%, min    98.00%,   2 3D sequences,     0 alignment sequences, 1850 random sequences,   37 random matches, 10 NTs, cWW-tWW-L-tWW-cWW-L
Sensitivity 100.00%, Specificity  98.00%, Minimum  98.00% using method 8
Number of false positives with core edit > 0 is 37
1 * Deficit + 3 * Core Edit <= 21.5435
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_77658.1'
                     Signature: {'cWW-cWW-cWW-cWW'  ''}
                         NumNT: 8
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 34
                      Truncate: 5
                      NumFixed: 16
                      OwnScore: [-6.0645 -4.3416 -4.3416 -4.7813 -4.7813 -7.3237 -5.1325 -4.7241 -4.3416 -4.7241 -4.3416 -6.5027 -5.1059 … ]
                   OwnSequence: {1×34 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 9 8 8 8]
            MeanSequenceLength: 8.0294
               DeficitEditData: [5442×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

34 sequences from 3D structures
Using 5442 random sequences, 0 from an alignment, and 34 from 3D structures
Group 318, IL_77658.1  has acceptance rules AlignmentScore >= -24.3416, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  14.2501
TP   100.00%, TN    96.00%, min    96.00%,  34 3D sequences,     0 alignment sequences, 5420 random sequences,  217 random matches,  8 NTs, cWW-cWW-cWW-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 217
1 * Deficit + 3 * Core Edit <= 9.9086
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11
Motif index 12
Motif index 13
Motif index 14
Motif index 15
Motif index 16
Motif index 17
Motif index 18
Motif index 19
Motif index 20
Motif index 21
Motif index 22
Motif index 23
Motif index 24
Motif index 25
Motif index 26
Motif index 27
Motif index 28
Motif index 29
Motif index 30
Motif index 31
Motif index 32
Motif index 33
Motif index 34


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_77691.5'
                     Signature: {'cWW-tSH-L-R-L-cWW'  ''}
                         NumNT: 9
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 7
                      Truncate: 6
                      NumFixed: 20
                      OwnScore: [-6.7254 -6.7254 -7.1963 -7.4645 -7.4190 -7.1963 -6.9732]
                   OwnSequence: {'CGAAG*UUAG'  'CGAAG*UUAG'  'CGGAA*UGAG'  'CGAAG*CGAG'  'GAAAG*UAAC'  'CGGAA*UGAG'  'CAAAG*UGAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 9 9 9 9 9]
            MeanSequenceLength: 9
               DeficitEditData: [8543×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

7 sequences from 3D structures
Using 8543 random sequences, 0 from an alignment, and 7 from 3D structures
Group 319, IL_77691.5  has acceptance rules AlignmentScore >= -26.7254, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.4976
TP   100.00%, TN    96.00%, min    96.00%,   7 3D sequences,     0 alignment sequences, 8504 random sequences,  340 random matches,  9 NTs, cWW-tSH-L-R-L-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 340
1 * Deficit + 3 * Core Edit <= 9.7721
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_77870.1'
                     Signature: {'cWW-L-R-L-tHS-L-cWW-L-cWW'  ''}
                         NumNT: 13
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 11
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 9
                      NumFixed: 30
                      OwnScore: [-10.0100 -8.2020]
                   OwnSequence: {'CUCUCAUC*GUGCG'  'CCUGAAUC*GUGAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [13 13]
            MeanSequenceLength: 13
               DeficitEditData: [3452×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 3452 random sequences, 0 from an alignment, and 2 from 3D structures
Decreased cutoff from  22.0235 because the cutoff seemed overly generous
Group 320, IL_77870.1  has acceptance rules AlignmentScore >= -28.2020, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  28.5831
TP   100.00%, TN    98.00%, min    98.00%,   2 3D sequences,     0 alignment sequences, 3452 random sequences,   69 random matches, 13 NTs, cWW-L-R-L-tHS-L-cWW-L-cWW
Sensitivity 100.00%, Specificity  98.00%, Minimum  98.00% using method 8
Number of false positives with core edit > 0 is 69
1 * Deficit + 3 * Core Edit <= 20.3811
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_78349.3'
                     Signature: {'cWW-L-R-L-R-L-R-L-cWW-L-L'  ''}
                         NumNT: 13
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 12
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 9
                      NumFixed: 42
                      OwnScore: [-10.1204 -10.1221]
                   OwnSequence: {'UGAAAGAC*GGGGAG'  'UGAAAUCC*GAACUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [14 14]
            MeanSequenceLength: 14
               DeficitEditData: [5776×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 5776 random sequences, 0 from an alignment, and 2 from 3D structures
Decreased cutoff from  20.1438 because the cutoff seemed overly generous
Group 321, IL_78349.3  has acceptance rules AlignmentScore >= -30.1204, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  30.1204
TP   100.00%, TN    96.12%, min    96.12%,   2 3D sequences,     0 alignment sequences, 5776 random sequences,  224 random matches, 13 NTs, cWW-L-R-L-R-L-R-L-cWW-L-L
Sensitivity 100.00%, Specificity  96.12%, Minimum  96.12% using method 8
Number of false positives with core edit > 0 is 224
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_78472.1'
                     Signature: {'cWW-L-R-L-R-L-R-L-cWW-L-L'  ''}
                         NumNT: 13
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 11
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 9
                      NumFixed: 36
                      OwnScore: -9.0330
                   OwnSequence: {'GGCGGAAA*UGGGC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 13
            MeanSequenceLength: 13
               DeficitEditData: [3244×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 3244 random sequences, 0 from an alignment, and 1 from 3D structures
Group 322, IL_78472.1  has acceptance rules AlignmentScore >= -29.0330, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  28.9992
TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences, 3244 random sequences,  130 random matches, 13 NTs, cWW-L-R-L-R-L-R-L-cWW-L-L
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 130
1 * Deficit + 3 * Core Edit <= 19.9662
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_78800.1'
                     Signature: {'cWW-cSH-L-cWW'  ''}
                         NumNT: 6
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 5
                      NumFixed: 20
                      OwnScore: [-4.8895 -4.8895]
                   OwnSequence: {'UUCU*AAUA'  'UUCU*AAUA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8]
            MeanSequenceLength: 8
               DeficitEditData: [7342×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 7342 random sequences, 0 from an alignment, and 2 from 3D structures
Group 323, IL_78800.1  has acceptance rules AlignmentScore >= -24.8895, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.9592
TP   100.00%, TN    95.99%, min    95.99%,   2 3D sequences,     0 alignment sequences, 7339 random sequences,  294 random matches,  6 NTs, cWW-cSH-L-cWW
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 294
1 * Deficit + 3 * Core Edit <= 12.0696
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_79846.1'
                     Signature: {'cWW-R-L-L-tWH-cWW-L-L-L-R-L-R-cSH-L-L'  ''}
                         NumNT: 19
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 12
                        NumBPh: 2
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 17
                      NumFixed: 38
                      OwnScore: -11.4084
                   OwnSequence: {'UAGUAGUGCAACCGAC*GAA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 19
            MeanSequenceLength: 19
               DeficitEditData: [18.5490 5]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 1 random sequences, 0 from an alignment, and 1 from 3D structures
Group 324, IL_79846.1  has acceptance rules AlignmentScore >= -31.4084, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  36.4084
TP   100.00%, TN   100.00%, min   100.00%,   1 3D sequences,     0 alignment sequences,    1 random sequences,    0 random matches, 19 NTs, cWW-R-L-L-tWH-cWW-L-L-L-R-L-R-cSH-L-L
Sensitivity 100.00%, Specificity 100.00%, Minimum 100.00% using method 1
Number of false positives with core edit > 0 is 0
1 * Deficit + 3 * Core Edit <= 25.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_79895.1'
                     Signature: {'cWW-L-cWW-L'  ''}
                         NumNT: 6
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 5
                      NumFixed: 20
                      OwnScore: [-5.0280 -5.0284]
                   OwnSequence: {'GUCC*GC'  'GAUU*AC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6]
            MeanSequenceLength: 6
               DeficitEditData: [9747×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 9747 random sequences, 0 from an alignment, and 2 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 325, IL_79895.1  has acceptance rules AlignmentScore >= -25.0280, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  14.5280
TP   100.00%, TN    83.78%, min    83.78%,   2 3D sequences,     0 alignment sequences, 9669 random sequences, 1568 random matches,  6 NTs, cWW-L-cWW-L
Sensitivity 100.00%, Specificity  83.78%, Minimum  83.78% using method 11
Number of false positives with core edit > 0 is 1568
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_80209.1'
                     Signature: {'cWW-cHW-L-cWW-L-L-R-L-R-L'  ''}
                         NumNT: 13
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 11
                      NumFixed: 42
                      OwnScore: -9.0533
                   OwnSequence: {'UGAUUAGCGAC*GGA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 14
            MeanSequenceLength: 14
               DeficitEditData: [2757×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 2757 random sequences, 0 from an alignment, and 1 from 3D structures
Group 326, IL_80209.1  has acceptance rules AlignmentScore >= -29.0533, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  29.0418
TP   100.00%, TN    96.01%, min    96.01%,   1 3D sequences,     0 alignment sequences, 2757 random sequences,  110 random matches, 13 NTs, cWW-cHW-L-cWW-L-L-R-L-R-L
Sensitivity 100.00%, Specificity  96.01%, Minimum  96.01% using method 6
Number of false positives with core edit > 0 is 110
1 * Deficit + 3 * Core Edit <= 19.9884
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_80231.1'
                     Signature: {'cWW-L-R-L-R-L-R-tHS-cWW'  ''}
                         NumNT: 11
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 11
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 7
                      NumFixed: 22
                      OwnScore: [-10.2618 -9.1226]
                   OwnSequence: {'GAUGAAA*UAACC'  'AAGAAG*CCACU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [12 11]
            MeanSequenceLength: 11.5000
               DeficitEditData: [8622×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 8622 random sequences, 0 from an alignment, and 2 from 3D structures
Group 327, IL_80231.1  has acceptance rules AlignmentScore >= -29.1226, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.5089
TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 8622 random sequences,  345 random matches, 11 NTs, cWW-L-R-L-R-L-R-tHS-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 345
1 * Deficit + 3 * Core Edit <= 16.3862
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_80298.1'
                     Signature: {'cWW-L-cWW-L-L-R-L-R-L-R-L-R-L-R-L-R-L-R-L-R-L-R'  ''}
                         NumNT: 24
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 16
                        NumBPh: 1
                         NumBR: 2
                  NumInstances: 1
                      Truncate: 23
                      NumFixed: 92
                      OwnScore: -17.8619
                   OwnSequence: {'CAGGGGAUUGAAAAUUCCGAGU*AUAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 26
            MeanSequenceLength: 26
               DeficitEditData: [0×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 0 random sequences, 0 from an alignment, and 1 from 3D structures
No random sequence matches, so essentially no model-specific cutoff imposed
Decreased cutoff to  25.0000 so that it is possible to reject matches
Group 328, IL_80298.1  has acceptance rules AlignmentScore >= -37.8619, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  42.8619
TP   100.00%, TN      NaN%, min   100.00%,   1 3D sequences,     0 alignment sequences,    0 random sequences,    0 random matches, 24 NTs, cWW-L-cWW-L-L-R-L-R-L-R-L-R-L-R-L-R-L-R-L-R-L-R
Sensitivity 100.00%, Specificity    NaN%, Minimum 100.00% using method 12
Number of false positives with core edit > 0 is 0
1 * Deficit + 3 * Core Edit <= 25.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_80398.1'
                     Signature: {'cWW-L-cSW-L-R-cWW'  ''}
                         NumNT: 8
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 5
                      NumFixed: 28
                      OwnScore: -5.2704
                   OwnSequence: {'GAAA*UAAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 8
            MeanSequenceLength: 8
               DeficitEditData: [10528×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 10528 random sequences, 0 from an alignment, and 1 from 3D structures
Group 329, IL_80398.1  has acceptance rules AlignmentScore >= -25.2704, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.7925
TP   100.00%, TN    95.92%, min    95.92%,   1 3D sequences,     0 alignment sequences, 10513 random sequences,  429 random matches,  8 NTs, cWW-L-cSW-L-R-cWW
Sensitivity 100.00%, Specificity  95.92%, Minimum  95.92% using method 6
Number of false positives with core edit > 0 is 429
1 * Deficit + 3 * Core Edit <= 10.5220
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_80412.1'
                     Signature: {'cWW-tSW-L-cWW-L-L-R-L'  ''}
                         NumNT: 11
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 9
                      NumFixed: 34
                      OwnScore: -8.1335
                   OwnSequence: {'AGCCUCCA*UAAU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 12
            MeanSequenceLength: 12
               DeficitEditData: [3373×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 3373 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  20.4421 because the cutoff seemed overly generous
Group 330, IL_80412.1  has acceptance rules AlignmentScore >= -28.1335, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  28.1335
TP   100.00%, TN    96.32%, min    96.32%,   1 3D sequences,     0 alignment sequences, 3373 random sequences,  124 random matches, 11 NTs, cWW-tSW-L-cWW-L-L-R-L
Sensitivity 100.00%, Specificity  96.32%, Minimum  96.32% using method 8
Number of false positives with core edit > 0 is 124
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_80604.6'
                     Signature: {'cWW-cWW-tWH-tWH-tHW-tHW-cWW'  ''}
                         NumNT: 14
                  NumBasepairs: 7
                    Structured: 1
                     NumStacks: 15
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 3
                      Truncate: 8
                      NumFixed: 22
                      OwnScore: [-8.2485 -7.1671 -7.1671]
                   OwnSequence: {'GUAUAAC*GCUAAUAC'  'GGAUAAC*GCUAAUAC'  'GGAUAAC*GCUAAUAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [15 15 15]
            MeanSequenceLength: 15
               DeficitEditData: [804×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 804 random sequences, 0 from an alignment, and 3 from 3D structures
Decreased cutoff from  23.3764 because the cutoff seemed overly generous
Group 331, IL_80604.6  has acceptance rules AlignmentScore >= -27.1671, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  29.1322
TP   100.00%, TN    98.01%, min    98.01%,   3 3D sequences,     0 alignment sequences,  804 random sequences,   16 random matches, 14 NTs, cWW-cWW-tWH-tWH-tHW-tHW-cWW
Sensitivity 100.00%, Specificity  98.01%, Minimum  98.01% using method 8
Number of false positives with core edit > 0 is 16
1 * Deficit + 3 * Core Edit <= 21.9651
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_80926.1'
                     Signature: {'cWW-cWW-tSH-tHS-L-cWW'  ''}
                         NumNT: 11
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 7
                      Truncate: 7
                      NumFixed: 22
                      OwnScore: [-6.3453 -6.3453 -6.3453 -6.3453 -6.8266 -6.3453 -6.3453]
                   OwnSequence: {1×7 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [12 12 12 12 12 12 12]
            MeanSequenceLength: 12
               DeficitEditData: [4212×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

7 sequences from 3D structures
Using 4212 random sequences, 0 from an alignment, and 7 from 3D structures
Group 332, IL_80926.1  has acceptance rules AlignmentScore >= -26.3453, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.5946
TP   100.00%, TN    96.01%, min    96.01%,   7 3D sequences,     0 alignment sequences, 4212 random sequences,  168 random matches, 11 NTs, cWW-cWW-tSH-tHS-L-cWW
Sensitivity 100.00%, Specificity  96.01%, Minimum  96.01% using method 6
Number of false positives with core edit > 0 is 168
1 * Deficit + 3 * Core Edit <= 19.2493
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_81392.1'
                     Signature: {'cWW-L-R-L-R-L-cWW-L-L-R-L'  ''}
                         NumNT: 13
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 10
                      NumFixed: 48
                      OwnScore: -16.2142
                   OwnSequence: {'CCCCUUUCCG*CUACACACUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 20
            MeanSequenceLength: 20
               DeficitEditData: [0×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 0 random sequences, 0 from an alignment, and 1 from 3D structures
No random sequence matches, so essentially no model-specific cutoff imposed
Decreased cutoff to  25.0000 so that it is possible to reject matches
Group 333, IL_81392.1  has acceptance rules AlignmentScore >= -36.2142, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  41.2142
TP   100.00%, TN      NaN%, min   100.00%,   1 3D sequences,     0 alignment sequences,    0 random sequences,    0 random matches, 13 NTs, cWW-L-R-L-R-L-cWW-L-L-R-L
Sensitivity 100.00%, Specificity    NaN%, Minimum 100.00% using method 12
Number of false positives with core edit > 0 is 0
1 * Deficit + 3 * Core Edit <= 25.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_81516.2'
                     Signature: {'cWW-cWS-tSH-L-tWH-cWW-tSS-tSH-L-R-L'  ''}
                         NumNT: 16
                  NumBasepairs: 9
                    Structured: 1
                     NumStacks: 14
                        NumBPh: 3
                         NumBR: 2
                  NumInstances: 6
                      Truncate: 13
                      NumFixed: 38
                      OwnScore: [-6.0432 -6.8905 -7.6790 -6.7486 -7.7971 -7.7971]
                   OwnSequence: {1×6 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [18 18 18 18 18 18]
            MeanSequenceLength: 18
               DeficitEditData: [59×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

6 sequences from 3D structures
Using 59 random sequences, 0 from an alignment, and 6 from 3D structures
Decreased cutoff from  25.0937 because the cutoff seemed overly generous
Group 334, IL_81516.2  has acceptance rules AlignmentScore >= -26.0432, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  28.8404
TP   100.00%, TN    98.31%, min    98.31%,   6 3D sequences,     0 alignment sequences,   59 random sequences,    1 random matches, 16 NTs, cWW-cWS-tSH-L-tWH-cWW-tSS-tSH-L-R-L
Sensitivity 100.00%, Specificity  98.31%, Minimum  98.31% using method 8
Number of false positives with core edit > 0 is 1
1 * Deficit + 3 * Core Edit <= 22.7971
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_81522.2'
                     Signature: {'cWW-L-L-cWW'  ''}
                         NumNT: 6
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 2
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 3
                      Truncate: 5
                      NumFixed: 24
                      OwnScore: [-6.3660 -6.3660 -9.5309]
                   OwnSequence: {'GUUAC*GUUC'  'GUUAC*GUUC'  'UAGGC*GG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 7]
            MeanSequenceLength: 8.3333
               DeficitEditData: [17680×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 17680 random sequences, 0 from an alignment, and 3 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 335, IL_81522.2  has acceptance rules AlignmentScore >= -26.3660, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.8660
TP   100.00%, TN    95.28%, min    95.28%,   3 3D sequences,     0 alignment sequences, 17660 random sequences,  834 random matches,  6 NTs, cWW-L-L-cWW
Sensitivity 100.00%, Specificity  95.28%, Minimum  95.28% using method 11
Number of false positives with core edit > 0 is 834
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_81731.1'
                     Signature: {'cWW-cWW-L-R-L-R-L-cWW-L-tWW-L-R-L'  ''}
                         NumNT: 17
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 13
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 13
                      NumFixed: 38
                      OwnScore: -11.6226
                   OwnSequence: {'GGCUAAAGAGUG*CAGAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 17
            MeanSequenceLength: 17
               DeficitEditData: [205×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 205 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  22.2285 because the cutoff seemed overly generous
Group 336, IL_81731.1  has acceptance rules AlignmentScore >= -31.6226, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  32.0670
TP   100.00%, TN    98.05%, min    98.05%,   1 3D sequences,     0 alignment sequences,  205 random sequences,    4 random matches, 17 NTs, cWW-cWW-L-R-L-R-L-cWW-L-tWW-L-R-L
Sensitivity 100.00%, Specificity  98.05%, Minimum  98.05% using method 8
Number of false positives with core edit > 0 is 4
1 * Deficit + 3 * Core Edit <= 20.4444
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_81831.1'
                     Signature: {'cWW-L-cWW'  ''}
                         NumNT: 5
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 2
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 4
                      NumFixed: 16
                      OwnScore: [-5.5044 -4.8112]
                   OwnSequence: {'UAAG*CA'  'GUA*UC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 5]
            MeanSequenceLength: 5.5000
               DeficitEditData: [10395×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 10395 random sequences, 0 from an alignment, and 2 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 337, IL_81831.1  has acceptance rules AlignmentScore >= -24.8112, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  14.3112
TP   100.00%, TN    78.74%, min    78.74%,   2 3D sequences,     0 alignment sequences, 10049 random sequences, 2136 random matches,  5 NTs, cWW-L-cWW
Sensitivity 100.00%, Specificity  78.74%, Minimum  78.74% using method 11
Number of false positives with core edit > 0 is 2136
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_82107.4'
                     Signature: {'cWW-cWW'  ''}
                         NumNT: 4
                  NumBasepairs: 2
                    Structured: 0
                     NumStacks: 2
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 30
                      Truncate: 3
                      NumFixed: 12
                      OwnScore: [-6.2514 -6.2514 -5.7199 -5.7199 -5.9582 -6.2514 -5.8879 -4.4918 -4.4918 -6.5678 -4.4918 -6.5678 -4.6241 … ]
                   OwnSequence: {1×30 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 7 7]
            MeanSequenceLength: 6.0667
               DeficitEditData: [9533×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

30 sequences from 3D structures
Using 9533 random sequences, 0 from an alignment, and 30 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 338, IL_82107.4  has acceptance rules AlignmentScore >= -24.4918, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.9918
TP   100.00%, TN    78.62%, min    78.62%,  30 3D sequences,     0 alignment sequences, 8714 random sequences, 1863 random matches,  4 NTs, cWW-cWW
Sensitivity 100.00%, Specificity  78.62%, Minimum  78.62% using method 11
Number of false positives with core edit > 0 is 1863
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11
Motif index 12
Motif index 13
Motif index 14
Motif index 15
Motif index 16
Motif index 17
Motif index 18
Motif index 19
Motif index 20
Motif index 21
Motif index 22
Motif index 23
Motif index 24
Motif index 25
Motif index 26
Motif index 27
Motif index 28
Motif index 29
Motif index 30


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_82292.1'
                     Signature: {'cWW-L-R-L-R-L-R-L-R-cWW'  ''}
                         NumNT: 12
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 11
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 3
                      Truncate: 7
                      NumFixed: 32
                      OwnScore: [-10.8989 -10.2013 -12.4874]
                   OwnSequence: {'CGCAAG*CGCAAG'  'CCUUGG*CCUUGG'  'UACAGA*UAGGUA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [12 12 12]
            MeanSequenceLength: 12
               DeficitEditData: [9404×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 9404 random sequences, 0 from an alignment, and 3 from 3D structures
Group 339, IL_82292.1  has acceptance rules AlignmentScore >= -30.2013, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.8474
TP   100.00%, TN    96.00%, min    96.00%,   3 3D sequences,     0 alignment sequences, 9404 random sequences,  376 random matches, 12 NTs, cWW-L-R-L-R-L-R-L-R-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 376
1 * Deficit + 3 * Core Edit <= 16.6461
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_82426.6'
                     Signature: {'cWW-cHW-R-L-cHW-cHW-cHW-L-cWW-R'  ''}
                         NumNT: 14
                  NumBasepairs: 7
                    Structured: 1
                     NumStacks: 13
                        NumBPh: 1
                         NumBR: 2
                  NumInstances: 6
                      Truncate: 10
                      NumFixed: 36
                      OwnScore: [-6.3293 -5.7415 -6.3293 -5.7415 -5.7415 -5.7415]
                   OwnSequence: {1×6 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [16 16 16 16 16 16]
            MeanSequenceLength: 16
               DeficitEditData: [81×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

6 sequences from 3D structures
Using 81 random sequences, 0 from an alignment, and 6 from 3D structures
Decreased cutoff from  23.3607 because the cutoff seemed overly generous
Group 340, IL_82426.6  has acceptance rules AlignmentScore >= -25.7415, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  27.4034
TP   100.00%, TN    97.53%, min    97.53%,   6 3D sequences,     0 alignment sequences,   81 random sequences,    2 random matches, 14 NTs, cWW-cHW-R-L-cHW-cHW-cHW-L-cWW-R
Sensitivity 100.00%, Specificity  97.53%, Minimum  97.53% using method 8
Number of false positives with core edit > 0 is 2
1 * Deficit + 3 * Core Edit <= 21.6619
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_82683.2'
                     Signature: {'cWW-L-R-L-cWW-L'  ''}
                         NumNT: 8
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 11
                      Truncate: 6
                      NumFixed: 28
                      OwnScore: [-3.2651 -3.2651 -3.2651 -3.2651 -3.2651 -3.2651 -3.2651 -3.2651 -3.2651 -3.2651 -3.2651]
                   OwnSequence: {1×11 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10 10 10 10 10 10 10 10 10 10]
            MeanSequenceLength: 10
               DeficitEditData: [7448×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

11 sequences from 3D structures
Using 7448 random sequences, 0 from an alignment, and 11 from 3D structures
Group 341, IL_82683.2  has acceptance rules AlignmentScore >= -23.2651, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  20.6068
TP   100.00%, TN    96.00%, min    96.00%,  11 3D sequences,     0 alignment sequences, 7447 random sequences,  298 random matches,  8 NTs, cWW-L-R-L-cWW-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 298
1 * Deficit + 3 * Core Edit <= 17.3417
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_82706.1'
                     Signature: {'cWW-L-R-L-cWW'  ''}
                         NumNT: 7
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 5
                      NumFixed: 24
                      OwnScore: [-5.9736 -5.9736]
                   OwnSequence: {'UCUUUGG*CGA'  'UCUUUGG*CGA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10]
            MeanSequenceLength: 10
               DeficitEditData: [12088×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 12088 random sequences, 0 from an alignment, and 2 from 3D structures
Group 342, IL_82706.1  has acceptance rules AlignmentScore >= -25.9736, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.5382
TP   100.00%, TN    95.99%, min    95.99%,   2 3D sequences,     0 alignment sequences, 12088 random sequences,  485 random matches,  7 NTs, cWW-L-R-L-cWW
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 485
1 * Deficit + 3 * Core Edit <= 18.5645
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_82741.2'
                     Signature: {'cWW-L-cWW-L-L'  ''}
                         NumNT: 7
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 3
                      Truncate: 6
                      NumFixed: 24
                      OwnScore: [-5.8801 -5.8801 -8.4785]
                   OwnSequence: {'CAACG*UUG'  'CAACG*UUG'  'CCCUU*AG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8 7]
            MeanSequenceLength: 7.6667
               DeficitEditData: [14098×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 14098 random sequences, 0 from an alignment, and 3 from 3D structures
Group 343, IL_82741.2  has acceptance rules AlignmentScore >= -25.8801, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.8736
TP   100.00%, TN    96.00%, min    96.00%,   3 3D sequences,     0 alignment sequences, 14085 random sequences,  563 random matches,  7 NTs, cWW-L-cWW-L-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 563
1 * Deficit + 3 * Core Edit <= 9.9935
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_82968.1'
                     Signature: {'cWW-L-cWW-L-L-R-L-R-L'  ''}
                         NumNT: 11
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 10
                      NumFixed: 40
                      OwnScore: [-6.3500 -6.3500]
                   OwnSequence: {'CGGAGGCAC*GG'  'CGGAGGCAC*GG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11]
            MeanSequenceLength: 11
               DeficitEditData: [6763×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 6763 random sequences, 0 from an alignment, and 2 from 3D structures
Group 344, IL_82968.1  has acceptance rules AlignmentScore >= -26.3500, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.6028
TP   100.00%, TN    95.99%, min    95.99%,   2 3D sequences,     0 alignment sequences, 6763 random sequences,  271 random matches, 11 NTs, cWW-L-cWW-L-L-R-L-R-L
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 271
1 * Deficit + 3 * Core Edit <= 18.2527
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_83149.1'
                     Signature: {'cWW-tSH-tHH-L-R-L-R-L-R-L-R-L-R-L-R-L-cWW-L-cWW'  ''}
                         NumNT: 24
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 19
                        NumBPh: 4
                         NumBR: 2
                  NumInstances: 2
                      Truncate: 14
                      NumFixed: 74
                      OwnScore: [-14.6354 -14.6354]
                   OwnSequence: {'UGAAAAUGGAUGGCGC*GACACCACAAAA'  'UGAAAAUGGAUGGCGC*GACACCACAAAA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [28 28]
            MeanSequenceLength: 28
               DeficitEditData: [0×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 0 random sequences, 0 from an alignment, and 2 from 3D structures
No random sequence matches, so essentially no model-specific cutoff imposed
Decreased cutoff to  25.0000 so that it is possible to reject matches
Group 345, IL_83149.1  has acceptance rules AlignmentScore >= -34.6354, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  39.6354
TP   100.00%, TN      NaN%, min   100.00%,   2 3D sequences,     0 alignment sequences,    0 random sequences,    0 random matches, 24 NTs, cWW-tSH-tHH-L-R-L-R-L-R-L-R-L-R-L-R-L-cWW-L-cWW
Sensitivity 100.00%, Specificity    NaN%, Minimum 100.00% using method 12
Number of false positives with core edit > 0 is 0
1 * Deficit + 3 * Core Edit <= 25.0000
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_83150.2'
                     Signature: {'cWW-tHH-cWW-L-L'  ''}
                         NumNT: 7
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 4
                      Truncate: 6
                      NumFixed: 24
                      OwnScore: [-5.8464 -5.8464 -6.1547 -6.1547]
                   OwnSequence: {'GGAAG*CGC'  'GGAAG*CGC'  'UAAUU*ACCA'  'UAAUU*ACCA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8 9 9]
            MeanSequenceLength: 8.5000
               DeficitEditData: [7282×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 7282 random sequences, 0 from an alignment, and 4 from 3D structures
Group 346, IL_83150.2  has acceptance rules AlignmentScore >= -25.8464, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.5743
TP   100.00%, TN    95.98%, min    95.98%,   4 3D sequences,     0 alignment sequences, 7257 random sequences,  292 random matches,  7 NTs, cWW-tHH-cWW-L-L
Sensitivity 100.00%, Specificity  95.98%, Minimum  95.98% using method 6
Number of false positives with core edit > 0 is 292
1 * Deficit + 3 * Core Edit <= 9.7279
Motif index 1
Motif index 2
Motif index 3
Motif index 4


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_83389.2'
                     Signature: {'cWW-cWW'  ''}
                         NumNT: 4
                  NumBasepairs: 2
                    Structured: 0
                     NumStacks: 0
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 5
                      Truncate: 3
                      NumFixed: 12
                      OwnScore: [-5.7185 -6.0550 -6.0550 -6.1545 -6.1545]
                   OwnSequence: {'AAG*CUAU'  'ACG*CUAU'  'ACG*CUAU'  'GAA*UACC'  'GAA*UACC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 7 7 7 7]
            MeanSequenceLength: 7
               DeficitEditData: [11017×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

5 sequences from 3D structures
Using 11017 random sequences, 0 from an alignment, and 5 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 347, IL_83389.2  has acceptance rules AlignmentScore >= -25.7185, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.2185
TP   100.00%, TN    90.10%, min    90.10%,   5 3D sequences,     0 alignment sequences, 10968 random sequences, 1086 random matches,  4 NTs, cWW-cWW
Sensitivity 100.00%, Specificity  90.10%, Minimum  90.10% using method 11
Number of false positives with core edit > 0 is 1086
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_84251.1'
                     Signature: {'cWW-L-tHS-cWW'  ''}
                         NumNT: 8
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 5
                      NumFixed: 16
                      OwnScore: [-6.9051 -9.4912]
                   OwnSequence: {'UCCG*UCCG'  'CAAG*CGAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 9]
            MeanSequenceLength: 8.5000
               DeficitEditData: [9528×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 9528 random sequences, 0 from an alignment, and 2 from 3D structures
Group 348, IL_84251.1  has acceptance rules AlignmentScore >= -26.9051, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.4630
TP   100.00%, TN    95.99%, min    95.99%,   2 3D sequences,     0 alignment sequences, 9519 random sequences,  382 random matches,  8 NTs, cWW-L-tHS-cWW
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 382
1 * Deficit + 3 * Core Edit <= 10.5579
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_84409.1'
                     Signature: {'cWW-tSS-L-cWH-L-cSH-cHW-tWH-cSS-tWH-tSW-cWS-R-L-R-cSH-R-cWW-L'  ''}
                         NumNT: 23
                  NumBasepairs: 15
                    Structured: 1
                     NumStacks: 20
                        NumBPh: 4
                         NumBR: 2
                  NumInstances: 1
                      Truncate: 14
                      NumFixed: 50
                      OwnScore: -14.6431
                   OwnSequence: {'CACAGUGACGAAGU*AGUGGAACGCG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 25
            MeanSequenceLength: 25
               DeficitEditData: [0×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 0 random sequences, 0 from an alignment, and 1 from 3D structures
No random sequence matches, so essentially no model-specific cutoff imposed
Decreased cutoff to  25.0000 so that it is possible to reject matches
Group 349, IL_84409.1  has acceptance rules AlignmentScore >= -34.6431, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  39.6431
TP   100.00%, TN      NaN%, min   100.00%,   1 3D sequences,     0 alignment sequences,    0 random sequences,    0 random matches, 23 NTs, cWW-tSS-L-cWH-L-cSH-cHW-tWH-cSS-tWH-tSW-cWS-R-L-R-cSH-R-cWW-L
Sensitivity 100.00%, Specificity    NaN%, Minimum 100.00% using method 12
Number of false positives with core edit > 0 is 0
1 * Deficit + 3 * Core Edit <= 25.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_84476.1'
                     Signature: {'cWW-cWW'  ''}
                         NumNT: 4
                  NumBasepairs: 2
                    Structured: 0
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 13
                      Truncate: 3
                      NumFixed: 12
                      OwnScore: [-4.2784 -4.2784 -5.7068 -4.2784 -5.7068 -4.2784 -7.7194 -8.7864 -8.7864 -7.5379 -5.9691 -4.5440 -9.1073]
                   OwnSequence: {1×13 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 6 6 6 6 6 7 7 6 6 6 6]
            MeanSequenceLength: 6.1538
               DeficitEditData: [11963×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

13 sequences from 3D structures
Using 11963 random sequences, 0 from an alignment, and 13 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 350, IL_84476.1  has acceptance rules AlignmentScore >= -24.2784, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.7784
TP   100.00%, TN    90.37%, min    90.37%,  13 3D sequences,     0 alignment sequences, 11584 random sequences, 1116 random matches,  4 NTs, cWW-cWW
Sensitivity 100.00%, Specificity  90.37%, Minimum  90.37% using method 11
Number of false positives with core edit > 0 is 1116
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11
Motif index 12
Motif index 13


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_84665.1'
                     Signature: {'cWW-L-cSW-cWW-L-L-R-L-R-L-R-L'  ''}
                         NumNT: 15
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 13
                      NumFixed: 50
                      OwnScore: -10.8969
                   OwnSequence: {'CCACAGCAGAAG*CAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 15
            MeanSequenceLength: 15
               DeficitEditData: [1398×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 1398 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  20.0663 because the cutoff seemed overly generous
Group 351, IL_84665.1  has acceptance rules AlignmentScore >= -30.8969, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  30.8969
TP   100.00%, TN    96.57%, min    96.57%,   1 3D sequences,     0 alignment sequences, 1398 random sequences,   48 random matches, 15 NTs, cWW-L-cSW-cWW-L-L-R-L-R-L-R-L
Sensitivity 100.00%, Specificity  96.57%, Minimum  96.57% using method 8
Number of false positives with core edit > 0 is 48
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_84694.2'
                     Signature: {'cWW-L-R-tSH-tHW-tHH-tHS-cWW-cWW'  ''}
                         NumNT: 16
                  NumBasepairs: 7
                    Structured: 1
                     NumStacks: 19
                        NumBPh: 3
                         NumBR: 1
                  NumInstances: 3
                      Truncate: 9
                      NumFixed: 30
                      OwnScore: [-9.8383 -9.8383 -11.5994]
                   OwnSequence: {'CUGAACUU*AUCAAUAAG'  'CUGAACUU*AUCAAUAAG'  'GAGAACUG*CUUAGUACC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [17 17 17]
            MeanSequenceLength: 17
               DeficitEditData: [317×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 317 random sequences, 0 from an alignment, and 3 from 3D structures
Decreased cutoff from  23.2773 because the cutoff seemed overly generous
Group 352, IL_84694.2  has acceptance rules AlignmentScore >= -29.8383, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  31.4696
TP   100.00%, TN    98.11%, min    98.11%,   3 3D sequences,     0 alignment sequences,  317 random sequences,    6 random matches, 16 NTs, cWW-L-R-tSH-tHW-tHH-tHS-cWW-cWW
Sensitivity 100.00%, Specificity  98.11%, Minimum  98.11% using method 8
Number of false positives with core edit > 0 is 6
1 * Deficit + 3 * Core Edit <= 21.6313
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_85033.2'
                     Signature: {'cWW-cWW-cWW-cWW'  ''}
                         NumNT: 8
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 35
                      Truncate: 5
                      NumFixed: 16
                      OwnScore: [-7.2002 -7.2002 -8.3304 -8.3304 -7.2002 -7.2002 -10.3826 -7.2002 -9.3405 -8.3526 -8.3047 -6.9488 … ]
                   OwnSequence: {1×35 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 9 9 9 9 9 9 9]
            MeanSequenceLength: 8.2000
               DeficitEditData: [7892×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

35 sequences from 3D structures
Using 7892 random sequences, 0 from an alignment, and 35 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 353, IL_85033.2  has acceptance rules AlignmentScore >= -26.3446, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.8446
TP   100.00%, TN    89.38%, min    89.38%,  35 3D sequences,     0 alignment sequences, 7747 random sequences,  823 random matches,  8 NTs, cWW-cWW-cWW-cWW
Sensitivity 100.00%, Specificity  89.38%, Minimum  89.38% using method 11
Number of false positives with core edit > 0 is 823
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11
Motif index 12
Motif index 13
Motif index 14
Motif index 15
Motif index 16
Motif index 17
Motif index 18
Motif index 19
Motif index 20
Motif index 21
Motif index 22
Motif index 23
Motif index 24
Motif index 25
Motif index 26
Motif index 27
Motif index 28
Motif index 29
Motif index 30
Motif index 31
Motif index 32
Motif index 33
Motif index 34
Motif index 35


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_85222.1'
                     Signature: {'cWW-L-R-L-R-L-cWW-L-L'  ''}
                         NumNT: 11
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 8
                      NumFixed: 40
                      OwnScore: -8.7794
                   OwnSequence: {'GGCACUC*GUUGC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 12
            MeanSequenceLength: 12
               DeficitEditData: [7418×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 7418 random sequences, 0 from an alignment, and 1 from 3D structures
Group 354, IL_85222.1  has acceptance rules AlignmentScore >= -28.7794, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  27.8815
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 7418 random sequences,  297 random matches, 11 NTs, cWW-L-R-L-R-L-cWW-L-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 297
1 * Deficit + 3 * Core Edit <= 19.1021
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_85498.1'
                     Signature: {'cWW-L-R-L-cWW-L-L-R-L-R'  ''}
                         NumNT: 12
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 10
                      NumFixed: 44
                      OwnScore: -8.5936
                   OwnSequence: {'UGGCGAACAG*CGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 13
            MeanSequenceLength: 13
               DeficitEditData: [4753×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 4753 random sequences, 0 from an alignment, and 1 from 3D structures
Group 355, IL_85498.1  has acceptance rules AlignmentScore >= -28.5936, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  28.2537
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 4753 random sequences,  190 random matches, 12 NTs, cWW-L-R-L-cWW-L-L-R-L-R
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 190
1 * Deficit + 3 * Core Edit <= 19.6601
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_85536.2'
                     Signature: {'cWW-tSH-L-R-tHS-cWW-cWW'  ''}
                         NumNT: 12
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 13
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 8
                      Truncate: 7
                      NumFixed: 20
                      OwnScore: [-9.2052 -9.2052 -8.9304 -8.9304 -9.0418 -9.0418 -11.2640 -20.6055]
                   OwnSequence: {1×8 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [12 12 12 12 12 12 12 14]
            MeanSequenceLength: 12.2500
               DeficitEditData: [5552×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

8 sequences from 3D structures
Using 5552 random sequences, 0 from an alignment, and 8 from 3D structures
Group 356, IL_85536.2  has acceptance rules AlignmentScore >= -28.9304, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.0452
TP   100.00%, TN    96.00%, min    96.00%,   8 3D sequences,     0 alignment sequences, 5552 random sequences,  222 random matches, 12 NTs, cWW-tSH-L-R-tHS-cWW-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 222
1 * Deficit + 3 * Core Edit <= 16.1148
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_85599.2'
                     Signature: {'cWW-tHS-cWW'  ''}
                         NumNT: 6
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 9
                      Truncate: 4
                      NumFixed: 14
                      OwnScore: [-4.8583 -4.8583 -4.9976 -4.8583 -4.9976 -5.6752 -5.8145 -5.8145 -7.0993]
                   OwnSequence: {'UAG*UGGG'  'UAG*UGGG'  'UAG*CGGG'  'UAG*UGGG'  'UAG*CGGG'  'CAG*UGGG'  'CAG*CGGG'  'CAG*CGGG'  'UAU*AGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 7 7 7 7 7 7 7 6]
            MeanSequenceLength: 6.8889
               DeficitEditData: [7116×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

9 sequences from 3D structures
Using 7116 random sequences, 0 from an alignment, and 9 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 357, IL_85599.2  has acceptance rules AlignmentScore >= -24.8583, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  14.3583
TP   100.00%, TN    90.20%, min    90.20%,   9 3D sequences,     0 alignment sequences, 6929 random sequences,  679 random matches,  6 NTs, cWW-tHS-cWW
Sensitivity 100.00%, Specificity  90.20%, Minimum  90.20% using method 11
Number of false positives with core edit > 0 is 679
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_85630.1'
                     Signature: {'cWW-tSH-L-R-L-R-L-cWW-L-cWW-L'  ''}
                         NumNT: 15
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 13
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 10
                      NumFixed: 44
                      OwnScore: -9.5416
                   OwnSequence: {'UGCAUCCGC*GAGUAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 15
            MeanSequenceLength: 15
               DeficitEditData: [631×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 631 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  23.1147 because the cutoff seemed overly generous
Group 358, IL_85630.1  has acceptance rules AlignmentScore >= -29.5416, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  31.6214
TP   100.00%, TN    97.94%, min    97.94%,   1 3D sequences,     0 alignment sequences,  631 random sequences,   13 random matches, 15 NTs, cWW-tSH-L-R-L-R-L-cWW-L-cWW-L
Sensitivity 100.00%, Specificity  97.94%, Minimum  97.94% using method 8
Number of false positives with core edit > 0 is 13
1 * Deficit + 3 * Core Edit <= 22.0798
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_85652.1'
                     Signature: {'cWW-tSH-L-R-L-R-L-cWW-L'  ''}
                         NumNT: 12
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 3
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 8
                      NumFixed: 38
                      OwnScore: -7.5971
                   OwnSequence: {'UGAACCG*CAAAA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 12
            MeanSequenceLength: 12
               DeficitEditData: [6253×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 6253 random sequences, 0 from an alignment, and 1 from 3D structures
Group 359, IL_85652.1  has acceptance rules AlignmentScore >= -27.5971, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.6826
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 6253 random sequences,  250 random matches, 12 NTs, cWW-tSH-L-R-L-R-L-cWW-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 250
1 * Deficit + 3 * Core Edit <= 19.0856
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_85879.1'
                     Signature: {'cWW-L-R-tHW-tHW-L-R-L-R-cWW-cWW'  ''}
                         NumNT: 16
                  NumBasepairs: 8
                    Structured: 1
                     NumStacks: 16
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 9
                      NumFixed: 24
                      OwnScore: -10.7851
                   OwnSequence: {'GGAUAAUGGC*GACGAUAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 18
            MeanSequenceLength: 18
               DeficitEditData: [56×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 56 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  21.3567 because the cutoff seemed overly generous
Group 360, IL_85879.1  has acceptance rules AlignmentScore >= -30.7851, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  30.7851
TP   100.00%, TN    98.21%, min    98.21%,   1 3D sequences,     0 alignment sequences,   56 random sequences,    1 random matches, 16 NTs, cWW-L-R-tHW-tHW-L-R-L-R-cWW-cWW
Sensitivity 100.00%, Specificity  98.21%, Minimum  98.21% using method 8
Number of false positives with core edit > 0 is 1
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_86012.1'
                     Signature: {'cWW-tHS-tWH-cWH-cWW-L-L-cWW'  ''}
                         NumNT: 13
                  NumBasepairs: 7
                    Structured: 1
                     NumStacks: 11
                        NumBPh: 0
                         NumBR: 2
                  NumInstances: 1
                      Truncate: 8
                      NumFixed: 34
                      OwnScore: -8.2480
                   OwnSequence: {'UCUGUGAUG*UGCAUGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 16
            MeanSequenceLength: 16
               DeficitEditData: [89×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 89 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  25.4934 because the cutoff seemed overly generous
Group 361, IL_86012.1  has acceptance rules AlignmentScore >= -28.2480, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  32.9190
TP   100.00%, TN    97.75%, min    97.75%,   1 3D sequences,     0 alignment sequences,   89 random sequences,    2 random matches, 13 NTs, cWW-tHS-tWH-cWH-cWW-L-L-cWW
Sensitivity 100.00%, Specificity  97.75%, Minimum  97.75% using method 8
Number of false positives with core edit > 0 is 2
1 * Deficit + 3 * Core Edit <= 24.6710
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_86136.1'
                     Signature: {'cWW-tSH-L-cWW-L-L-R-L'  ''}
                         NumNT: 11
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 1
                         NumBR: 2
                  NumInstances: 1
                      Truncate: 9
                      NumFixed: 34
                      OwnScore: -6.5775
                   OwnSequence: {'CGAGGAAC*GAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 11
            MeanSequenceLength: 11
               DeficitEditData: [8870×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 8870 random sequences, 0 from an alignment, and 1 from 3D structures
Group 362, IL_86136.1  has acceptance rules AlignmentScore >= -26.5775, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.5468
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 8869 random sequences,  355 random matches, 11 NTs, cWW-tSH-L-cWW-L-L-R-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 355
1 * Deficit + 3 * Core Edit <= 17.9693
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_87211.1'
                     Signature: {'cWW-cSW-L-cWW-L'  ''}
                         NumNT: 7
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 6
                      NumFixed: 26
                      OwnScore: -4.7096
                   OwnSequence: {'CAUCAG*UG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 8
            MeanSequenceLength: 8
               DeficitEditData: [9878×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 9878 random sequences, 0 from an alignment, and 1 from 3D structures
Group 363, IL_87211.1  has acceptance rules AlignmentScore >= -24.7096, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  18.1266
TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences, 9875 random sequences,  396 random matches,  7 NTs, cWW-cSW-L-cWW-L
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 396
1 * Deficit + 3 * Core Edit <= 13.4169
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_87284.1'
                     Signature: {'cWW-tSH-tHW-tWH-tHS-cWW'  ''}
                         NumNT: 12
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 11
                        NumBPh: 0
                         NumBR: 2
                  NumInstances: 3
                      Truncate: 7
                      NumFixed: 20
                      OwnScore: [-9.0745 -9.0745 -12.1567]
                   OwnSequence: {'UCACAG*UCACAG'  'UCACAG*UCACAG'  'CGAAAG*CGAAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [12 12 12]
            MeanSequenceLength: 12
               DeficitEditData: [3393×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 3393 random sequences, 0 from an alignment, and 3 from 3D structures
Group 364, IL_87284.1  has acceptance rules AlignmentScore >= -29.0745, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.0265
TP   100.00%, TN    95.99%, min    95.99%,   3 3D sequences,     0 alignment sequences, 3393 random sequences,  136 random matches, 12 NTs, cWW-tSH-tHW-tWH-tHS-cWW
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 136
1 * Deficit + 3 * Core Edit <= 15.9520
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_87290.1'
                     Signature: {'cWW-L-R-L-R-L-R-L-R-L-R-L-R-L-R-L'  ''}
                         NumNT: 15
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 13
                      NumFixed: 58
                      OwnScore: -13.4677
                   OwnSequence: {'CCGACCUUGAAAUAC*GGAGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 20
            MeanSequenceLength: 20
               DeficitEditData: [19×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 19 random sequences, 0 from an alignment, and 1 from 3D structures
Group 365, IL_87290.1  has acceptance rules AlignmentScore >= -33.4677, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  38.4677
TP   100.00%, TN    94.74%, min    94.74%,   1 3D sequences,     0 alignment sequences,   19 random sequences,    1 random matches, 15 NTs, cWW-L-R-L-R-L-R-L-R-L-R-L-R-L-R-L
Sensitivity 100.00%, Specificity  94.74%, Minimum  94.74% using method 1
Number of false positives with core edit > 0 is 1
1 * Deficit + 3 * Core Edit <= 25.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_87907.2'
                     Signature: {'cWW-cWW-cWW'  ''}
                         NumNT: 6
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 179
                      Truncate: 4
                      NumFixed: 14
                      OwnScore: [-4.2523 -4.7465 -4.7465 -4.7465 -4.7465 -4.0146 -4.1113 -4.2523 -5.7817 -3.7634 -4.1113 -3.7634 -4.7965 … ]
                   OwnSequence: {1×179 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 … ]
            MeanSequenceLength: 6.0335
               DeficitEditData: [5474×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

179 sequences from 3D structures
Using 5474 random sequences, 0 from an alignment, and 179 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 366, IL_87907.2  has acceptance rules AlignmentScore >= -23.7634, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.2634
TP   100.00%, TN    89.51%, min    89.51%, 179 3D sequences,     0 alignment sequences, 4765 random sequences,  500 random matches,  6 NTs, cWW-cWW-cWW
Sensitivity 100.00%, Specificity  89.51%, Minimum  89.51% using method 11
Number of false positives with core edit > 0 is 500
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11
Motif index 12
Motif index 13
Motif index 14
Motif index 15
Motif index 16
Motif index 17
Motif index 18
Motif index 19
Motif index 20
Motif index 21
Motif index 22
Motif index 23
Motif index 24
Motif index 25
Motif index 26
Motif index 27
Motif index 28
Motif index 29
Motif index 30
Motif index 31
Motif index 32
Motif index 33
Motif index 34
Motif index 35
Motif index 36
Motif index 37
Motif index 38
Motif index 39
Motif index 40
Motif index 41
Motif index 42
Motif index 43
Motif index 44
Motif index 45
Motif index 46
Motif index 47
Motif index 48
Motif index 49
Motif index 50
Motif index 51
Motif index 52
Motif index 53
Motif index 54
Motif index 55
Motif index 56
Motif index 57
Motif index 58
Motif index 59
Motif index 60
Motif index 61
Motif index 62
Motif index 63
Motif index 64
Motif index 65
Motif index 66
Motif index 67
Motif index 68
Motif index 69
Motif index 70
Motif index 71
Motif index 72
Motif index 73
Motif index 74
Motif index 75
Motif index 76
Motif index 77
Motif index 78
Motif index 79
Motif index 80
Motif index 81
Motif index 82
Motif index 83
Motif index 84
Motif index 85
Motif index 86
Motif index 87
Motif index 88
Motif index 89
Motif index 90
Motif index 91
Motif index 92
Motif index 93
Motif index 94
Motif index 95
Motif index 96
Motif index 97
Motif index 98
Motif index 99
Motif index 100
Motif index 101
Motif index 102
Motif index 103
Motif index 104
Motif index 105
Motif index 106
Motif index 107
Motif index 108
Motif index 109
Motif index 110
Motif index 111
Motif index 112
Motif index 113
Motif index 114
Motif index 115
Motif index 116
Motif index 117
Motif index 118
Motif index 119
Motif index 120
Motif index 121
Motif index 122
Motif index 123
Motif index 124
Motif index 125
Motif index 126
Motif index 127
Motif index 128
Motif index 129
Motif index 130
Motif index 131
Motif index 132
Motif index 133
Motif index 134
Motif index 135
Motif index 136
Motif index 137
Motif index 138
Motif index 139
Motif index 140
Motif index 141
Motif index 142
Motif index 143
Motif index 144
Motif index 145
Motif index 146
Motif index 147
Motif index 148
Motif index 149
Motif index 150
Motif index 151
Motif index 152
Motif index 153
Motif index 154
Motif index 155
Motif index 156
Motif index 157
Motif index 158
Motif index 159
Motif index 160
Motif index 161
Motif index 162
Motif index 163
Motif index 164
Motif index 165
Motif index 166
Motif index 167
Motif index 168
Motif index 169
Motif index 170
Motif index 171
Motif index 172
Motif index 173
Motif index 174
Motif index 175
Motif index 176
Motif index 177
Motif index 178
Motif index 179


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_88017.1'
                     Signature: {'cWW-L-cWW-L-L-R-L'  ''}
                         NumNT: 9
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 7
                      Truncate: 8
                      NumFixed: 32
                      OwnScore: [-2.6289 -2.6289 -2.6289 -2.6289 -2.6289 -2.6289 -2.6289]
                   OwnSequence: {'GAACUAC*GC'  'GAACUAC*GC'  'GAACUAC*GC'  'GAACUAC*GC'  'GAACUAC*GC'  'GAACUAC*GC'  'GAACUAC*GC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 9 9 9 9 9]
            MeanSequenceLength: 9
               DeficitEditData: [5072×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

7 sequences from 3D structures
Using 5072 random sequences, 0 from an alignment, and 7 from 3D structures
Group 367, IL_88017.1  has acceptance rules AlignmentScore >= -22.6289, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  18.4926
TP   100.00%, TN    95.98%, min    95.98%,   7 3D sequences,     0 alignment sequences, 5070 random sequences,  204 random matches,  9 NTs, cWW-L-cWW-L-L-R-L
Sensitivity 100.00%, Specificity  95.98%, Minimum  95.98% using method 6
Number of false positives with core edit > 0 is 204
1 * Deficit + 3 * Core Edit <= 15.8637
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_88072.1'
                     Signature: {'cWW-L-R-L-cWW-L-L-R-L-R-L'  ''}
                         NumNT: 13
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 11
                      NumFixed: 34
                      OwnScore: -6.9414
                   OwnSequence: {'AAAAGCAUAG*CCU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 13
            MeanSequenceLength: 13
               DeficitEditData: [1807×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 1807 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  21.4376 because the cutoff seemed overly generous
Group 368, IL_88072.1  has acceptance rules AlignmentScore >= -26.9414, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.9414
TP   100.00%, TN    97.68%, min    97.68%,   1 3D sequences,     0 alignment sequences, 1807 random sequences,   42 random matches, 13 NTs, cWW-L-R-L-cWW-L-L-R-L-R-L
Sensitivity 100.00%, Specificity  97.68%, Minimum  97.68% using method 8
Number of false positives with core edit > 0 is 42
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_88082.1'
                     Signature: {'cWW-L-tSS-L-cWW-L'  ''}
                         NumNT: 8
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 6
                      NumFixed: 22
                      OwnScore: [-6.5137 -6.5137]
                   OwnSequence: {'GAUUAAG*CGC'  'GAUUAAG*CGC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10]
            MeanSequenceLength: 10
               DeficitEditData: [13273×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 13273 random sequences, 0 from an alignment, and 2 from 3D structures
Group 369, IL_88082.1  has acceptance rules AlignmentScore >= -26.5137, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  22.2095
TP   100.00%, TN    95.96%, min    95.96%,   2 3D sequences,     0 alignment sequences, 13272 random sequences,  536 random matches,  8 NTs, cWW-L-tSS-L-cWW-L
Sensitivity 100.00%, Specificity  95.96%, Minimum  95.96% using method 6
Number of false positives with core edit > 0 is 536
1 * Deficit + 3 * Core Edit <= 15.6958
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_88116.2'
                     Signature: {'cWW-tSH-L-R-L-R-L-R-cWW-cWW'  ''}
                         NumNT: 14
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 12
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 3
                      Truncate: 8
                      NumFixed: 40
                      OwnScore: [-8.5392 -8.5392 -9.9489]
                   OwnSequence: {'UCAAAGU*AACCAAG'  'UCAAAGU*AACCAAG'  'UGAACAC*GACGAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [14 14 14]
            MeanSequenceLength: 14
               DeficitEditData: [3375×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 3375 random sequences, 0 from an alignment, and 3 from 3D structures
Decreased cutoff from  20.3224 because the cutoff seemed overly generous
Group 370, IL_88116.2  has acceptance rules AlignmentScore >= -28.5392, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  28.5392
TP   100.00%, TN    96.27%, min    96.27%,   3 3D sequences,     0 alignment sequences, 3375 random sequences,  126 random matches, 14 NTs, cWW-tSH-L-R-L-R-L-R-cWW-cWW
Sensitivity 100.00%, Specificity  96.27%, Minimum  96.27% using method 8
Number of false positives with core edit > 0 is 126
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_88269.4'
                     Signature: {'cWW-tWW-cSH-tWH-tHS-cWW'  ''}
                         NumNT: 11
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 12
                        NumBPh: 2
                         NumBR: 1
                  NumInstances: 3
                      Truncate: 7
                      NumFixed: 24
                      OwnScore: [-8.2153 -8.1991 -7.6416]
                   OwnSequence: {'CGGUAC*GGACG'  'UAUGUAG*UGAAA'  'CGUUAC*GGAGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 12 11]
            MeanSequenceLength: 11.3333
               DeficitEditData: [7223×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 7223 random sequences, 0 from an alignment, and 3 from 3D structures
Group 371, IL_88269.4  has acceptance rules AlignmentScore >= -27.6416, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.3573
TP   100.00%, TN    96.00%, min    96.00%,   3 3D sequences,     0 alignment sequences, 7223 random sequences,  289 random matches, 11 NTs, cWW-tWW-cSH-tWH-tHS-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 289
1 * Deficit + 3 * Core Edit <= 17.7157
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_88974.1'
                     Signature: {'cWW-L-R-L-cWW-L-L-R-L-R'  ''}
                         NumNT: 12
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 10
                      NumFixed: 38
                      OwnScore: [-7.2458 -7.2458]
                   OwnSequence: {'UCGCGAGCAC*GGA'  'UCGCGAGCAC*GGA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [13 13]
            MeanSequenceLength: 13
               DeficitEditData: [3216×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 3216 random sequences, 0 from an alignment, and 2 from 3D structures
Decreased cutoff from  20.4677 because the cutoff seemed overly generous
Group 372, IL_88974.1  has acceptance rules AlignmentScore >= -27.2458, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  27.2458
TP   100.00%, TN    97.48%, min    97.48%,   2 3D sequences,     0 alignment sequences, 3216 random sequences,   81 random matches, 12 NTs, cWW-L-R-L-cWW-L-L-R-L-R
Sensitivity 100.00%, Specificity  97.48%, Minimum  97.48% using method 8
Number of false positives with core edit > 0 is 81
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_89021.2'
                     Signature: {'cWW-L-R-L-R-tHS-cWW'  ''}
                         NumNT: 10
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 11
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 6
                      Truncate: 6
                      NumFixed: 26
                      OwnScore: [-6.4807 -6.4807 -6.4807 -6.7461 -7.7279 -6.0068]
                   OwnSequence: {'CUAAG*CGAUG'  'CUAAG*CGAUG'  'CUAAG*CGAUG'  'UCAAG*CGAAG'  'UCAAG*UGAAG'  'UUAAG*CGAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10 10 10 10 10]
            MeanSequenceLength: 10
               DeficitEditData: [5983×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

6 sequences from 3D structures
Using 5983 random sequences, 0 from an alignment, and 6 from 3D structures
Group 373, IL_89021.2  has acceptance rules AlignmentScore >= -26.0068, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  18.6393
TP   100.00%, TN    96.00%, min    96.00%,   6 3D sequences,     0 alignment sequences, 5975 random sequences,  239 random matches, 10 NTs, cWW-L-R-L-R-tHS-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 239
1 * Deficit + 3 * Core Edit <= 12.6325
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_89047.1'
                     Signature: {'cWW-L-R-L-R-L-R-L-R-L-cWH-L-cWW'  ''}
                         NumNT: 16
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 16
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 10
                      NumFixed: 42
                      OwnScore: -9.7224
                   OwnSequence: {'CUUGGAUUUA*UUGUCAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 17
            MeanSequenceLength: 17
               DeficitEditData: [52×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 52 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  21.0446 because the cutoff seemed overly generous
Group 374, IL_89047.1  has acceptance rules AlignmentScore >= -29.7224, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  29.7224
TP   100.00%, TN    98.08%, min    98.08%,   1 3D sequences,     0 alignment sequences,   52 random sequences,    1 random matches, 16 NTs, cWW-L-R-L-R-L-R-L-R-L-cWH-L-cWW
Sensitivity 100.00%, Specificity  98.08%, Minimum  98.08% using method 8
Number of false positives with core edit > 0 is 1
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_89099.1'
                     Signature: {'cWW-L-R-L-R-L-R-L-R-cWW'  ''}
                         NumNT: 12
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 7
                      NumFixed: 20
                      OwnScore: -5.7275
                   OwnSequence: {'GGGAGC*GGGAGC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 12
            MeanSequenceLength: 12
               DeficitEditData: [1638×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 1638 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  20.4165 because the cutoff seemed overly generous
Group 375, IL_89099.1  has acceptance rules AlignmentScore >= -25.7275, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.7275
TP   100.00%, TN    96.34%, min    96.34%,   1 3D sequences,     0 alignment sequences, 1638 random sequences,   60 random matches, 12 NTs, cWW-L-R-L-R-L-R-L-R-cWW
Sensitivity 100.00%, Specificity  96.34%, Minimum  96.34% using method 8
Number of false positives with core edit > 0 is 60
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_89312.1'
                     Signature: {'cWW-tSH-L-cWS-cWW-L'  ''}
                         NumNT: 10
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 7
                      NumFixed: 24
                      OwnScore: -9.1602
                   OwnSequence: {'UGAAGGAAG*CAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 13
            MeanSequenceLength: 13
               DeficitEditData: [5005×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 5005 random sequences, 0 from an alignment, and 1 from 3D structures
Group 376, IL_89312.1  has acceptance rules AlignmentScore >= -29.1602, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  27.2406
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 5005 random sequences,  200 random matches, 10 NTs, cWW-tSH-L-cWS-cWW-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 200
1 * Deficit + 3 * Core Edit <= 18.0804
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_89505.4'
                     Signature: {'cWW-L-cWW'  ''}
                         NumNT: 5
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 117
                      Truncate: 4
                      NumFixed: 16
                      OwnScore: [-2.2793 -2.2793 -3.0650 -2.8529 -2.8529 -2.1490 -2.8529 -2.1490 -2.7865 -3.2934 -3.9309 -2.1490 -3.9309 … ]
                   OwnSequence: {1×117 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 … ]
            MeanSequenceLength: 5
               DeficitEditData: [4276×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

117 sequences from 3D structures
Using 4276 random sequences, 0 from an alignment, and 117 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 377, IL_89505.4  has acceptance rules AlignmentScore >= -22.1490, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  11.6490
TP   100.00%, TN    93.34%, min    93.34%, 117 3D sequences,     0 alignment sequences, 4027 random sequences,  268 random matches,  5 NTs, cWW-L-cWW
Sensitivity 100.00%, Specificity  93.34%, Minimum  93.34% using method 11
Number of false positives with core edit > 0 is 268
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11
Motif index 12
Motif index 13
Motif index 14
Motif index 15
Motif index 16
Motif index 17
Motif index 18
Motif index 19
Motif index 20
Motif index 21
Motif index 22
Motif index 23
Motif index 24
Motif index 25
Motif index 26
Motif index 27
Motif index 28
Motif index 29
Motif index 30
Motif index 31
Motif index 32
Motif index 33
Motif index 34
Motif index 35
Motif index 36
Motif index 37
Motif index 38
Motif index 39
Motif index 40
Motif index 41
Motif index 42
Motif index 43
Motif index 44
Motif index 45
Motif index 46
Motif index 47
Motif index 48
Motif index 49
Motif index 50
Motif index 51
Motif index 52
Motif index 53
Motif index 54
Motif index 55
Motif index 56
Motif index 57
Motif index 58
Motif index 59
Motif index 60
Motif index 61
Motif index 62
Motif index 63
Motif index 64
Motif index 65
Motif index 66
Motif index 67
Motif index 68
Motif index 69
Motif index 70
Motif index 71
Motif index 72
Motif index 73
Motif index 74
Motif index 75
Motif index 76
Motif index 77
Motif index 78
Motif index 79
Motif index 80
Motif index 81
Motif index 82
Motif index 83
Motif index 84
Motif index 85
Motif index 86
Motif index 87
Motif index 88
Motif index 89
Motif index 90
Motif index 91
Motif index 92
Motif index 93
Motif index 94
Motif index 95
Motif index 96
Motif index 97
Motif index 98
Motif index 99
Motif index 100
Motif index 101
Motif index 102
Motif index 103
Motif index 104
Motif index 105
Motif index 106
Motif index 107
Motif index 108
Motif index 109
Motif index 110
Motif index 111
Motif index 112
Motif index 113
Motif index 114
Motif index 115
Motif index 116
Motif index 117


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_89984.3'
                     Signature: {'cWW-L-R-L-cWW'  ''}
                         NumNT: 7
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: 5
                      NumFixed: 24
                      OwnScore: [-5.0144 -5.0144]
                   OwnSequence: {'GUACA*UUC'  'GUACU*AUC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8]
            MeanSequenceLength: 8
               DeficitEditData: [13954×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 13954 random sequences, 0 from an alignment, and 2 from 3D structures
Group 378, IL_89984.3  has acceptance rules AlignmentScore >= -25.0144, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.5655
TP   100.00%, TN    95.96%, min    95.96%,   2 3D sequences,     0 alignment sequences, 13951 random sequences,  563 random matches,  7 NTs, cWW-L-R-L-cWW
Sensitivity 100.00%, Specificity  95.96%, Minimum  95.96% using method 6
Number of false positives with core edit > 0 is 563
1 * Deficit + 3 * Core Edit <= 12.5511
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_90346.1'
                     Signature: {'cWW-L-R-L-cWW-L-L'  ''}
                         NumNT: 9
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 7
                      NumFixed: 32
                      OwnScore: -6.9106
                   OwnSequence: {'CUAAGC*GAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 10
            MeanSequenceLength: 10
               DeficitEditData: [16766×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 16766 random sequences, 0 from an alignment, and 1 from 3D structures
Group 379, IL_90346.1  has acceptance rules AlignmentScore >= -26.9106, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  22.1109
TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences, 16764 random sequences,  673 random matches,  9 NTs, cWW-L-R-L-cWW-L-L
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 673
1 * Deficit + 3 * Core Edit <= 15.2003
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_90351.1'
                     Signature: {'cWW-L-R-L-cWW'  ''}
                         NumNT: 7
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 8
                      Truncate: 5
                      NumFixed: 22
                      OwnScore: [-5.6455 -5.6455 -5.5754 -8.8725 -7.5305 -7.2287 -6.7222 -7.4202]
                   OwnSequence: {'GAAG*CAC'  'GAAG*CAC'  'CGAG*CGG'  'GAAUG*CGC'  'UCUC*GAA'  'UAAC*GUA'  'AAAC*GCU'  'GAUGG*CAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 7 7 8 7 7 7 8]
            MeanSequenceLength: 7.2500
               DeficitEditData: [11976×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

8 sequences from 3D structures
Using 11976 random sequences, 0 from an alignment, and 8 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 380, IL_90351.1  has acceptance rules AlignmentScore >= -25.5754, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.0754
TP   100.00%, TN    92.33%, min    92.33%,   8 3D sequences,     0 alignment sequences, 11844 random sequences,  909 random matches,  7 NTs, cWW-L-R-L-cWW
Sensitivity 100.00%, Specificity  92.33%, Minimum  92.33% using method 11
Number of false positives with core edit > 0 is 909
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_90729.1'
                     Signature: {'cWW-L-cWW'  ''}
                         NumNT: 5
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 30
                      Truncate: 4
                      NumFixed: 16
                      OwnScore: [-3.2250 -3.2250 -3.2250 -3.7365 -3.6013 -3.2250 -3.2250 -3.2250 -3.5860 -4.1849 -3.5860 -3.2250 -3.2250 … ]
                   OwnSequence: {1×30 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 6 5 5 5 5 5 6]
            MeanSequenceLength: 5.0667
               DeficitEditData: [6522×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

30 sequences from 3D structures
Using 6522 random sequences, 0 from an alignment, and 30 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 381, IL_90729.1  has acceptance rules AlignmentScore >= -23.2250, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  12.7250
TP   100.00%, TN    93.17%, min    93.17%,  30 3D sequences,     0 alignment sequences, 5444 random sequences,  372 random matches,  5 NTs, cWW-L-cWW
Sensitivity 100.00%, Specificity  93.17%, Minimum  93.17% using method 11
Number of false positives with core edit > 0 is 372
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11
Motif index 12
Motif index 13
Motif index 14
Motif index 15
Motif index 16
Motif index 17
Motif index 18
Motif index 19
Motif index 20
Motif index 21
Motif index 22
Motif index 23
Motif index 24
Motif index 25
Motif index 26
Motif index 27
Motif index 28
Motif index 29
Motif index 30


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_91592.1'
                     Signature: {'cWW-L-tHH-L-cWW-L-L'  ''}
                         NumNT: 10
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 2
                      Truncate: 8
                      NumFixed: 30
                      OwnScore: [-6.7044 -6.1070]
                   OwnSequence: {'CACGGCG*CGG'  'CACGGAG*CGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10]
            MeanSequenceLength: 10
               DeficitEditData: [10972×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 10972 random sequences, 0 from an alignment, and 2 from 3D structures
Group 382, IL_91592.1  has acceptance rules AlignmentScore >= -26.1070, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  23.0982
TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 10972 random sequences,  439 random matches, 10 NTs, cWW-L-tHH-L-cWW-L-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 439
1 * Deficit + 3 * Core Edit <= 16.9912
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_91636.1'
                     Signature: {'cWW-tSH-L-R-L-cWW-L-L'  ''}
                         NumNT: 11
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 3
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 8
                      NumFixed: 34
                      OwnScore: -5.4438
                   OwnSequence: {'GGGAACC*GUGC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 11
            MeanSequenceLength: 11
               DeficitEditData: [8115×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 8115 random sequences, 0 from an alignment, and 1 from 3D structures
Group 383, IL_91636.1  has acceptance rules AlignmentScore >= -25.4438, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.1540
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 8115 random sequences,  325 random matches, 11 NTs, cWW-tSH-L-R-L-cWW-L-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 325
1 * Deficit + 3 * Core Edit <= 19.7102
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_91698.1'
                     Signature: {'cWW-tWW-L-R-L-R-L-R-L-tHW-R-L-cWW'  ''}
                         NumNT: 17
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 12
                        NumBPh: 5
                         NumBR: 1
                  NumInstances: 2
                      Truncate: 10
                      NumFixed: 52
                      OwnScore: [-6.7285 -6.7285]
                   OwnSequence: {'UUGUGAAAC*GCCAGCGA'  'UUGUGAAAC*GCCAGCGA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [17 17]
            MeanSequenceLength: 17
               DeficitEditData: [72×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 72 random sequences, 0 from an alignment, and 2 from 3D structures
Decreased cutoff from  23.0796 because the cutoff seemed overly generous
Group 384, IL_91698.1  has acceptance rules AlignmentScore >= -26.7285, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.7285
TP   100.00%, TN    97.22%, min    97.22%,   2 3D sequences,     0 alignment sequences,   72 random sequences,    2 random matches, 17 NTs, cWW-tWW-L-R-L-R-L-R-L-tHW-R-L-cWW
Sensitivity 100.00%, Specificity  97.22%, Minimum  97.22% using method 8
Number of false positives with core edit > 0 is 2
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_91920.1'
                     Signature: {'cWW-cWW-tHH-cWW'  ''}
                         NumNT: 8
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 2
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 5
                      NumFixed: 16
                      OwnScore: -4.6055
                   OwnSequence: {'GUAAG*UAUC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 9
            MeanSequenceLength: 9
               DeficitEditData: [7648×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 7648 random sequences, 0 from an alignment, and 1 from 3D structures
Group 385, IL_91920.1  has acceptance rules AlignmentScore >= -24.6055, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  20.0156
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 7647 random sequences,  306 random matches,  8 NTs, cWW-cWW-tHH-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 306
1 * Deficit + 3 * Core Edit <= 15.4101
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_92446.2'
                     Signature: {'cWW-cWW-R-L-L'  ''}
                         NumNT: 7
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 5
                      Truncate: 5
                      NumFixed: 24
                      OwnScore: [-4.2259 -4.2259 -4.2259 -6.5720 -4.2259]
                   OwnSequence: {'CAUC*GUUG'  'CAUC*GUUG'  'CAUC*GUUG'  'UACC*GUGA'  'CAUC*GUUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8 8 8 8]
            MeanSequenceLength: 8
               DeficitEditData: [9291×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

5 sequences from 3D structures
Using 9291 random sequences, 0 from an alignment, and 5 from 3D structures
Group 386, IL_92446.2  has acceptance rules AlignmentScore >= -24.2259, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.2751
TP   100.00%, TN    95.95%, min    95.95%,   5 3D sequences,     0 alignment sequences, 9283 random sequences,  376 random matches,  7 NTs, cWW-cWW-R-L-L
Sensitivity 100.00%, Specificity  95.95%, Minimum  95.95% using method 6
Number of false positives with core edit > 0 is 376
1 * Deficit + 3 * Core Edit <= 11.0492
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_92634.2'
                     Signature: {'cWW-L-cWW-L-L'  ''}
                         NumNT: 7
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 1
                        NumBPh: 1
                         NumBR: 2
                  NumInstances: 3
                      Truncate: 6
                      NumFixed: 26
                      OwnScore: [-3.9771 -3.9771 -6.2337]
                   OwnSequence: {'AGUUGU*AU'  'AGUUGU*AU'  'CAAUGU*AG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8 8]
            MeanSequenceLength: 8
               DeficitEditData: [8827×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 8827 random sequences, 0 from an alignment, and 3 from 3D structures
Group 387, IL_92634.2  has acceptance rules AlignmentScore >= -23.9771, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.9305
TP   100.00%, TN    95.95%, min    95.95%,   3 3D sequences,     0 alignment sequences, 8817 random sequences,  357 random matches,  7 NTs, cWW-L-cWW-L-L
Sensitivity 100.00%, Specificity  95.95%, Minimum  95.95% using method 6
Number of false positives with core edit > 0 is 357
1 * Deficit + 3 * Core Edit <= 13.9534
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_93889.1'
                     Signature: {'cWW-R-tSH-L-cSH-L-L-R-L-R-L-R-L-R-L-R-L-L'  ''}
                         NumNT: 21
                  NumBasepairs: 7
                    Structured: 1
                     NumStacks: 18
                        NumBPh: 3
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 12
                      NumFixed: 58
                      OwnScore: -11.3153
                   OwnSequence: {'UGAAACGGCAG*UCAAUAGUAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 21
            MeanSequenceLength: 21
               DeficitEditData: [3×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 3 random sequences, 0 from an alignment, and 1 from 3D structures
Group 388, IL_93889.1  has acceptance rules AlignmentScore >= -31.3153, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  36.3153
TP   100.00%, TN    66.67%, min    66.67%,   1 3D sequences,     0 alignment sequences,    3 random sequences,    1 random matches, 21 NTs, cWW-R-tSH-L-cSH-L-L-R-L-R-L-R-L-R-L-R-L-L
Sensitivity 100.00%, Specificity  66.67%, Minimum  66.67% using method 1
Number of false positives with core edit > 0 is 1
1 * Deficit + 3 * Core Edit <= 25.0000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_94351.1'
                     Signature: {'cWW-L-R-L-R-L-tHS-cWW'  ''}
                         NumNT: 11
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 7
                      NumFixed: 28
                      OwnScore: -8.4815
                   OwnSequence: {'CUUGAA*UGGCG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 11
            MeanSequenceLength: 11
               DeficitEditData: [7675×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 7675 random sequences, 0 from an alignment, and 1 from 3D structures
Group 389, IL_94351.1  has acceptance rules AlignmentScore >= -28.4815, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.8235
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 7674 random sequences,  307 random matches, 11 NTs, cWW-L-R-L-R-L-tHS-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 307
1 * Deficit + 3 * Core Edit <= 17.3420
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_94684.1'
                     Signature: {'cWW-tWH-R-L-cWW-L-L'  ''}
                         NumNT: 9
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 2
                      Truncate: 7
                      NumFixed: 28
                      OwnScore: [-3.6421 -3.6421]
                   OwnSequence: {'UGGAAG*CUA'  'UGGAAG*CUA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9]
            MeanSequenceLength: 9
               DeficitEditData: [6264×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 6264 random sequences, 0 from an alignment, and 2 from 3D structures
Group 390, IL_94684.1  has acceptance rules AlignmentScore >= -23.6421, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  18.9149
TP   100.00%, TN    96.01%, min    96.01%,   2 3D sequences,     0 alignment sequences, 6259 random sequences,  250 random matches,  9 NTs, cWW-tWH-R-L-cWW-L-L
Sensitivity 100.00%, Specificity  96.01%, Minimum  96.01% using method 6
Number of false positives with core edit > 0 is 250
1 * Deficit + 3 * Core Edit <= 15.2728
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_94910.1'
                     Signature: {'cWW-tSS-tSH-L-R-R-L-cWW-L'  ''}
                         NumNT: 12
                  NumBasepairs: 7
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 3
                         NumBR: 2
                  NumInstances: 3
                      Truncate: 8
                      NumFixed: 30
                      OwnScore: [-9.3526 -7.1563 -7.2197]
                   OwnSequence: {'CUUUGACU*ACGAG'  'UGAUGACC*GCAAG'  'UGUUUGACG*CCGAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [13 13 14]
            MeanSequenceLength: 13.3333
               DeficitEditData: [1454×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 1454 random sequences, 0 from an alignment, and 3 from 3D structures
Decreased cutoff from  21.4482 because the cutoff seemed overly generous
Group 391, IL_94910.1  has acceptance rules AlignmentScore >= -27.1563, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  27.1563
TP   100.00%, TN    97.39%, min    97.39%,   3 3D sequences,     0 alignment sequences, 1454 random sequences,   38 random matches, 12 NTs, cWW-tSS-tSH-L-R-R-L-cWW-L
Sensitivity 100.00%, Specificity  97.39%, Minimum  97.39% using method 8
Number of false positives with core edit > 0 is 38
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_94967.1'
                     Signature: {'cWW-L-cWW-L'  ''}
                         NumNT: 6
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 2
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 5
                      NumFixed: 20
                      OwnScore: -5.2378
                   OwnSequence: {'GUUUC*GC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 7
            MeanSequenceLength: 7
               DeficitEditData: [12762×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 12762 random sequences, 0 from an alignment, and 1 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 392, IL_94967.1  has acceptance rules AlignmentScore >= -25.2378, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  14.7378
TP   100.00%, TN    95.15%, min    95.15%,   1 3D sequences,     0 alignment sequences, 12753 random sequences,  618 random matches,  6 NTs, cWW-L-cWW-L
Sensitivity 100.00%, Specificity  95.15%, Minimum  95.15% using method 11
Number of false positives with core edit > 0 is 618
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_95570.1'
                     Signature: {'cWW-cWH-R-L-cWW'  ''}
                         NumNT: 7
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 2
                      Truncate: 5
                      NumFixed: 24
                      OwnScore: [-6.3313 -6.5032]
                   OwnSequence: {'UGUUCG*CAG'  'UGCAG*CAA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 8]
            MeanSequenceLength: 8.5000
               DeficitEditData: [13420×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 13420 random sequences, 0 from an alignment, and 2 from 3D structures
Group 393, IL_95570.1  has acceptance rules AlignmentScore >= -26.3313, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  19.1640
TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 13416 random sequences,  537 random matches,  7 NTs, cWW-cWH-R-L-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 537
1 * Deficit + 3 * Core Edit <= 12.8327
Motif index 1
Motif index 2


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_95583.2'
                     Signature: {'cWW-L-cWW'  ''}
                         NumNT: 5
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 2
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 11
                      Truncate: 4
                      NumFixed: 20
                      OwnScore: [-3.8424 -3.8424 -4.4400 -4.6004 -4.6004 -4.6004 -3.8424 -5.8709 -7.0053 -8.1154 -5.8176]
                   OwnSequence: {1×11 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 6 6 6 6 6 6 7 7 6]
            MeanSequenceLength: 6.1818
               DeficitEditData: [8731×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

11 sequences from 3D structures
Using 8731 random sequences, 0 from an alignment, and 11 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 394, IL_95583.2  has acceptance rules AlignmentScore >= -23.8424, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.3424
TP   100.00%, TN    89.79%, min    89.79%,  11 3D sequences,     0 alignment sequences, 8463 random sequences,  864 random matches,  5 NTs, cWW-L-cWW
Sensitivity 100.00%, Specificity  89.79%, Minimum  89.79% using method 11
Number of false positives with core edit > 0 is 864
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8
Motif index 9
Motif index 10
Motif index 11


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_95727.1'
                     Signature: {'cWW-L-tSH-L-tHW-tHS-R-cWW-L'  ''}
                         NumNT: 14
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 11
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 9
                      NumFixed: 38
                      OwnScore: -9.5018
                   OwnSequence: {'CGCAGAUAC*GAGUAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 15
            MeanSequenceLength: 15
               DeficitEditData: [1285×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 1285 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  21.9335 because the cutoff seemed overly generous
Group 395, IL_95727.1  has acceptance rules AlignmentScore >= -29.5018, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  29.6962
TP   100.00%, TN    97.98%, min    97.98%,   1 3D sequences,     0 alignment sequences, 1285 random sequences,   26 random matches, 14 NTs, cWW-L-tSH-L-tHW-tHS-R-cWW-L
Sensitivity 100.00%, Specificity  97.98%, Minimum  97.98% using method 8
Number of false positives with core edit > 0 is 26
1 * Deficit + 3 * Core Edit <= 20.1944
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_95811.1'
                     Signature: {'cWW-L-cWW-L-cWW-L-R-L'  ''}
                         NumNT: 11
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 9
                      NumFixed: 34
                      OwnScore: -5.7537
                   OwnSequence: {'CGCAUAAC*GCG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 11
            MeanSequenceLength: 11
               DeficitEditData: [5616×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 5616 random sequences, 0 from an alignment, and 1 from 3D structures
Group 396, IL_95811.1  has acceptance rules AlignmentScore >= -25.7537, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.2472
TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences, 5616 random sequences,  225 random matches, 11 NTs, cWW-L-cWW-L-cWW-L-R-L
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 225
1 * Deficit + 3 * Core Edit <= 19.4935
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_96236.1'
                     Signature: {'cWW-tWW-cWW-L-cWW'  ''}
                         NumNT: 9
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 6
                      NumFixed: 24
                      OwnScore: -5.4083
                   OwnSequence: {'AAUUC*GUUAU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 10
            MeanSequenceLength: 10
               DeficitEditData: [5430×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 5430 random sequences, 0 from an alignment, and 1 from 3D structures
Group 397, IL_96236.1  has acceptance rules AlignmentScore >= -25.4083, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  22.3935
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 5430 random sequences,  217 random matches,  9 NTs, cWW-tWW-cWW-L-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 217
1 * Deficit + 3 * Core Edit <= 16.9851
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_96303.1'
                     Signature: {'cWW-cSH-tSW-tHW-cWW-L-L-R-L-R'  ''}
                         NumNT: 13
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 3
                      Truncate: 11
                      NumFixed: 42
                      OwnScore: [-9.3544 -9.3544 -10.6537]
                   OwnSequence: {'GUUGCGUCCGAAAG*CAC'  'GUUGCGUCCGAAAG*CAC'  'GUUACGUCCGAAAG*CAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [17 17 17]
            MeanSequenceLength: 17
               DeficitEditData: [108×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 108 random sequences, 0 from an alignment, and 3 from 3D structures
Decreased cutoff from  21.0688 because the cutoff seemed overly generous
Group 398, IL_96303.1  has acceptance rules AlignmentScore >= -29.3544, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  29.8428
TP   100.00%, TN    98.15%, min    98.15%,   3 3D sequences,     0 alignment sequences,  108 random sequences,    2 random matches, 13 NTs, cWW-cSH-tSW-tHW-cWW-L-L-R-L-R
Sensitivity 100.00%, Specificity  98.15%, Minimum  98.15% using method 8
Number of false positives with core edit > 0 is 2
1 * Deficit + 3 * Core Edit <= 20.4884
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_96332.5'
                     Signature: {'cWW-cWW-L-R-L-cWW-L'  ''}
                         NumNT: 10
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 7
                      Truncate: 7
                      NumFixed: 24
                      OwnScore: [-6.8222 -6.8222 -6.8222 -6.9497 -6.9497 -8.4295 -13.4630]
                   OwnSequence: {1×7 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11 11 11 11 11 10]
            MeanSequenceLength: 10.8571
               DeficitEditData: [11344×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

7 sequences from 3D structures
Using 11344 random sequences, 0 from an alignment, and 7 from 3D structures
Group 399, IL_96332.5  has acceptance rules AlignmentScore >= -26.8222, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  23.8909
TP   100.00%, TN    96.00%, min    96.00%,   7 3D sequences,     0 alignment sequences, 11344 random sequences,  454 random matches, 10 NTs, cWW-cWW-L-R-L-cWW-L
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 454
1 * Deficit + 3 * Core Edit <= 17.0687
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_96371.1'
                     Signature: {'cWW-tHH-cWW'  ''}
                         NumNT: 6
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 4
                      NumFixed: 14
                      OwnScore: -4.2663
                   OwnSequence: {'UAG*CGGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 7
            MeanSequenceLength: 7
               DeficitEditData: [9184×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 9184 random sequences, 0 from an alignment, and 1 from 3D structures
Group 400, IL_96371.1  has acceptance rules AlignmentScore >= -24.2663, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  14.0752
TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences, 9168 random sequences,  368 random matches,  6 NTs, cWW-tHH-cWW
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 368
1 * Deficit + 3 * Core Edit <= 9.8089
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_96759.1'
                     Signature: {'cWW-tSH-tWW-cWW'  ''}
                         NumNT: 8
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 5
                      NumFixed: 22
                      OwnScore: -4.8877
                   OwnSequence: {'CGAA*UUAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 8
            MeanSequenceLength: 8
               DeficitEditData: [4579×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 4579 random sequences, 0 from an alignment, and 1 from 3D structures
Group 401, IL_96759.1  has acceptance rules AlignmentScore >= -24.8877, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.5038
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 4574 random sequences,  183 random matches,  8 NTs, cWW-tSH-tWW-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 183
1 * Deficit + 3 * Core Edit <= 11.6161
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_96788.1'
                     Signature: {'cWW-tHW-tHS-cWW-cWW'  ''}
                         NumNT: 10
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 6
                      NumFixed: 18
                      OwnScore: -4.3375
                   OwnSequence: {'GAGGU*AAGUC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 10
            MeanSequenceLength: 10
               DeficitEditData: [3718×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 3718 random sequences, 0 from an alignment, and 1 from 3D structures
Group 402, IL_96788.1  has acceptance rules AlignmentScore >= -24.3375, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  22.3915
TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences, 3718 random sequences,  149 random matches, 10 NTs, cWW-tHW-tHS-cWW-cWW
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 149
1 * Deficit + 3 * Core Edit <= 18.0541
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_97273.1'
                     Signature: {'cWW-tSH-cWW-L-cWW-L'  ''}
                         NumNT: 9
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 3
                      Truncate: 7
                      NumFixed: 24
                      OwnScore: [-4.4505 -4.4505 -7.4256]
                   OwnSequence: {'GGGAUC*GUC'  'GGGAUC*GUC'  'GGUGCU*AAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 9]
            MeanSequenceLength: 9
               DeficitEditData: [5416×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 5416 random sequences, 0 from an alignment, and 3 from 3D structures
Group 403, IL_97273.1  has acceptance rules AlignmentScore >= -24.4505, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  18.4907
TP   100.00%, TN    95.99%, min    95.99%,   3 3D sequences,     0 alignment sequences, 5413 random sequences,  217 random matches,  9 NTs, cWW-tSH-cWW-L-cWW-L
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 217
1 * Deficit + 3 * Core Edit <= 14.0402
Motif index 1
Motif index 2
Motif index 3


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_97631.1'
                     Signature: {'cWW-L-R-L-R-L-tHS-cWW'  ''}
                         NumNT: 11
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 7
                      NumFixed: 22
                      OwnScore: -7.0325
                   OwnSequence: {'ACGAAU*AGACU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 11
            MeanSequenceLength: 11
               DeficitEditData: [6367×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 6367 random sequences, 0 from an alignment, and 1 from 3D structures
Group 404, IL_97631.1  has acceptance rules AlignmentScore >= -27.0325, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.4763
TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences, 6367 random sequences,  255 random matches, 11 NTs, cWW-L-R-L-R-L-tHS-cWW
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 255
1 * Deficit + 3 * Core Edit <= 17.4438
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_97697.1'
                     Signature: {'cWW-L-R-L-R-L-cWW-L-L'  ''}
                         NumNT: 11
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 4
                      Truncate: 8
                      NumFixed: 34
                      OwnScore: [-7.2338 -7.2338 -7.2338 -7.2338]
                   OwnSequence: {'AACUGAAU*ACAUU'  'AACUGAAU*ACAUU'  'AACUGAAU*ACAUU'  'AACUGAAU*ACAUU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [13 13 13 13]
            MeanSequenceLength: 13
               DeficitEditData: [4978×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 4978 random sequences, 0 from an alignment, and 4 from 3D structures
Decreased cutoff from  21.6770 because the cutoff seemed overly generous
Group 405, IL_97697.1  has acceptance rules AlignmentScore >= -27.2338, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  27.2338
TP   100.00%, TN    97.93%, min    97.93%,   4 3D sequences,     0 alignment sequences, 4978 random sequences,  103 random matches, 11 NTs, cWW-L-R-L-R-L-cWW-L-L
Sensitivity 100.00%, Specificity  97.93%, Minimum  97.93% using method 8
Number of false positives with core edit > 0 is 103
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1
Motif index 2
Motif index 3
Motif index 4


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_98347.1'
                     Signature: {'cWW-L-R-L-cWW'  ''}
                         NumNT: 7
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 5
                      NumFixed: 24
                      OwnScore: -6.7492
                   OwnSequence: {'GAAAAA*UAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 9
            MeanSequenceLength: 9
               DeficitEditData: [18347×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 18347 random sequences, 0 from an alignment, and 1 from 3D structures
Group 406, IL_98347.1  has acceptance rules AlignmentScore >= -26.7492, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  19.2035
TP   100.00%, TN    95.87%, min    95.87%,   1 3D sequences,     0 alignment sequences, 18346 random sequences,  757 random matches,  7 NTs, cWW-L-R-L-cWW
Sensitivity 100.00%, Specificity  95.87%, Minimum  95.87% using method 6
Number of false positives with core edit > 0 is 757
1 * Deficit + 3 * Core Edit <= 12.4544
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_99358.1'
                     Signature: {'cWW-L-R-L-cWW'  ''}
                         NumNT: 7
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 8
                      Truncate: 5
                      NumFixed: 24
                      OwnScore: [-7.1386 -7.0981 -7.0427 -7.1513 -7.5661 -8.5864 -8.8245 -9.1320]
                   OwnSequence: {'GAUG*CCC'  'GGUC*GGC'  'CCAG*CUG'  'UGUG*CUG'  'AUAG*CUU'  'UCCG*CAG'  'GAUC*GAAC'  'GAAA*UCGC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 7 7 7 7 7 8 8]
            MeanSequenceLength: 7.2500
               DeficitEditData: [11849×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

8 sequences from 3D structures
Using 11849 random sequences, 0 from an alignment, and 8 from 3D structures
Increased cutoff to   9.5000 so that at least a few sequences with core edit distance 1 can meet the cutoff
Group 407, IL_99358.1  has acceptance rules AlignmentScore >= -27.0427, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.5427
TP   100.00%, TN    79.67%, min    79.67%,   8 3D sequences,     0 alignment sequences, 11721 random sequences, 2383 random matches,  7 NTs, cWW-L-R-L-cWW
Sensitivity 100.00%, Specificity  79.67%, Minimum  79.67% using method 11
Number of false positives with core edit > 0 is 2383
1 * Deficit + 3 * Core Edit <= 9.5000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6
Motif index 7
Motif index 8


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_99380.1'
                     Signature: {'cWW-L-cWW-L-L-R'  ''}
                         NumNT: 8
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: 7
                      NumFixed: 28
                      OwnScore: -4.8115
                   OwnSequence: {'UUUCGA*UG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 8
            MeanSequenceLength: 8
               DeficitEditData: [9927×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 9927 random sequences, 0 from an alignment, and 1 from 3D structures
Group 408, IL_99380.1  has acceptance rules AlignmentScore >= -24.8115, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  19.2615
TP   100.00%, TN    95.77%, min    95.77%,   1 3D sequences,     0 alignment sequences, 9923 random sequences,  420 random matches,  8 NTs, cWW-L-cWW-L-L-R
Sensitivity 100.00%, Specificity  95.77%, Minimum  95.77% using method 6
Number of false positives with core edit > 0 is 420
1 * Deficit + 3 * Core Edit <= 14.4500
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_99498.1'
                     Signature: {'cWW-L-R-tHW-cWW'  ''}
                         NumNT: 8
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: 5
                      NumFixed: 22
                      OwnScore: -8.1525
                   OwnSequence: {'GCAUG*CUUACC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 11
            MeanSequenceLength: 11
               DeficitEditData: [9685×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 9685 random sequences, 0 from an alignment, and 1 from 3D structures
Group 409, IL_99498.1  has acceptance rules AlignmentScore >= -28.1525, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.0970
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 9685 random sequences,  387 random matches,  8 NTs, cWW-L-R-tHW-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 387
1 * Deficit + 3 * Core Edit <= 16.9445
Motif index 1


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_99646.2'
                     Signature: {'cWW-tWH-tHS-cWW'  ''}
                         NumNT: 8
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 6
                      Truncate: 5
                      NumFixed: 16
                      OwnScore: [-6.8563 -7.3671 -6.5247 -7.1352 -6.6244 -6.5247]
                   OwnSequence: {'CUAU*AAAUG'  'CUAU*AAACG'  'CUAG*CGAAG'  'AUAG*CGAGU'  'AUAG*CGAAU'  'CUAG*CGAUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 9 9 9 9]
            MeanSequenceLength: 9
               DeficitEditData: [9524×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

6 sequences from 3D structures
Using 9524 random sequences, 0 from an alignment, and 6 from 3D structures
Group 410, IL_99646.2  has acceptance rules AlignmentScore >= -26.5247, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.2623
TP   100.00%, TN    96.00%, min    96.00%,   6 3D sequences,     0 alignment sequences, 9508 random sequences,  380 random matches,  8 NTs, cWW-tWH-tHS-cWW
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 380
1 * Deficit + 3 * Core Edit <= 10.7376
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6


ans = 

  <a href="matlab:helpPopup struct" style="font-weight:bold">struct</a> with fields:

                       MotifID: 'IL_99692.2'
                     Signature: {'cWW-tSS-tSH-L-R-R-L-cWW-L-L'  ''}
                         NumNT: 13
                  NumBasepairs: 7
                    Structured: 1
                     NumStacks: 12
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 6
                      Truncate: 9
                      NumFixed: 34
                      OwnScore: [-8.3762 -7.8108 -7.8837 -7.9737 -7.8837 -8.2167]
                   OwnSequence: {1×6 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [14 14 14 14 14 14]
            MeanSequenceLength: 14
               DeficitEditData: [1728×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

6 sequences from 3D structures
Using 1728 random sequences, 0 from an alignment, and 6 from 3D structures
Decreased cutoff from  21.1063 because the cutoff seemed overly generous
Group 411, IL_99692.2  has acceptance rules AlignmentScore >= -27.8108, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  27.8108
TP   100.00%, TN    97.57%, min    97.57%,   6 3D sequences,     0 alignment sequences, 1728 random sequences,   42 random matches, 13 NTs, cWW-tSS-tSH-L-R-R-L-cWW-L-L
Sensitivity 100.00%, Specificity  97.57%, Minimum  97.57% using method 8
Number of false positives with core edit > 0 is 42
1 * Deficit + 3 * Core Edit <= 20.0000
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5
Motif index 6

 17 (  4.14%) models got the default cutoff from model size
  0 (  0.00%) models had their cutoff set by maximizing TP+TN
  0 (  0.00%) models got the default cutoff plus 2
  0 (  0.00%) models with cutoffs from TP+TN had the cutoff tightened to reduce false positives
  0 (  0.00%) models with default plus 2 had the cutoff tightened to reduce false positives
212 ( 51.58%) models had cutoff set from random sequences only
  0 (  0.00%) random cutoff models had their cutoff made more generous
101 ( 24.57%) random cutoff models had their cutoff made more restrictive
  0 (  0.00%) models had no random sequences and so no model-specific cutoff imposed
  0 (  0.00%) models had the cutoff set from alignment sequences only
 68 ( 16.55%) models got the minimum cutoff
411 groups, total in this table is 411
Group   1, IL_00225.13 has acceptance rules  -3.1718 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.1718 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    87.82%, min    87.82%,  49 3D sequences,     0 alignment sequences,  4565 random sequences,  556 random matches,  5 NTs, cWW-L-cWW
Group   2, IL_00555.1  has acceptance rules  -7.3179 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.3179 - AlignmentScore) +   3.0000 * CoreEdit <=  17.0787, method  6,TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 10349 random sequences,  414 random matches,  6 NTs, cWW-cWS-cWW-L-R
Group   3, IL_00881.1  has acceptance rules  -4.7734 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.7734 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    90.90%, min    90.90%,   2 3D sequences,     0 alignment sequences, 11656 random sequences, 1061 random matches,  6 NTs, cWW-L-cWW-L
Group   4, IL_00981.1  has acceptance rules  -4.3867 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.3867 - AlignmentScore) +   3.0000 * CoreEdit <=  17.4042, method  6,TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences,  4919 random sequences,  197 random matches, 10 NTs, cWW-tWH-tHH-tHS-cWW
Group   5, IL_01038.1  has acceptance rules  -6.8083 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.8083 - AlignmentScore) +   3.0000 * CoreEdit <=  16.7376, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences,  8202 random sequences,  328 random matches, 10 NTs, cWW-tWH-L-R-tHS-cWW
Group   6, IL_01176.1  has acceptance rules  -9.1223 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.1223 - AlignmentScore) +   3.0000 * CoreEdit <=  16.1489, method  6,TP   100.00%, TN    96.01%, min    96.01%,   1 3D sequences,     0 alignment sequences,  7387 random sequences,  295 random matches, 11 NTs, cWW-L-R-L-R-L-R-L-cWW
Group   7, IL_01488.3  has acceptance rules  -6.3878 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.3878 - AlignmentScore) +   3.0000 * CoreEdit <=  18.3766, method  6,TP   100.00%, TN    96.00%, min    96.00%,  10 3D sequences,     0 alignment sequences,  2627 random sequences,  105 random matches, 12 NTs, cWW-tSS-tSH-L-R-tHS-L-cWW
Group   8, IL_01994.1  has acceptance rules  -4.1444 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.1444 - AlignmentScore) +   3.0000 * CoreEdit <=  14.8334, method  6,TP   100.00%, TN    95.98%, min    95.98%,   3 3D sequences,     0 alignment sequences,  6513 random sequences,  262 random matches,  8 NTs, cWW-cWH-tHS-cWW-cSH-cWW
Group   9, IL_02203.1  has acceptance rules  -4.4173 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.4173 - AlignmentScore) +   3.0000 * CoreEdit <=  12.1170, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences,  5870 random sequences,  235 random matches,  8 NTs, cWW-cSW-cWW-cWW
Group  10, IL_02349.4  has acceptance rules  -6.0968 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.0968 - AlignmentScore) +   3.0000 * CoreEdit <=  20.1139, method  8,TP   100.00%, TN    97.98%, min    97.98%,   3 3D sequences,     0 alignment sequences,  1482 random sequences,   30 random matches, 13 NTs, cWW-tSH-tWH-cSH-tWH-tHS-cWW
Group  11, IL_02555.1  has acceptance rules  -2.3022 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -2.3022 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5677, method  6,TP   100.00%, TN    95.98%, min    95.98%,   9 3D sequences,     0 alignment sequences,  7368 random sequences,  296 random matches,  5 NTs, cWW-L-cWW
Group  12, IL_03109.3  has acceptance rules  -3.4885 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.4885 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    94.79%, min    94.79%,   6 3D sequences,     0 alignment sequences,  3897 random sequences,  203 random matches,  7 NTs, cWW-cWS-tWH-cWW-L
Group  13, IL_03350.1  has acceptance rules  -7.2950 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.2950 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.41%, min    97.41%,   3 3D sequences,     0 alignment sequences,   695 random sequences,   18 random matches, 13 NTs, cWW-tWH-cWW-L-L-cWW-L-L-L
Group  14, IL_04021.2  has acceptance rules  -6.1612 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.1612 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.65%, min    97.65%,   7 3D sequences,     0 alignment sequences,  1236 random sequences,   29 random matches, 14 NTs, cWW-L-R-tSH-tSH-tHS-cWW-cWW
Group  15, IL_04073.1  has acceptance rules -12.2606 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-12.2606 - AlignmentScore) +   3.0000 * CoreEdit <=  25.0000, method  1,TP   100.00%, TN   100.00%, min   100.00%,   1 3D sequences,     0 alignment sequences,     6 random sequences,    0 random matches, 18 NTs, cWW-L-R-L-tSH-L-R-cWW-L-R-R-L-cWW-L
Group  16, IL_04307.1  has acceptance rules -10.2277 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-10.2277 - AlignmentScore) +   3.0000 * CoreEdit <=  20.4127, method  8,TP   100.00%, TN    97.66%, min    97.66%,   1 3D sequences,     0 alignment sequences,   128 random sequences,    3 random matches, 16 NTs, cWW-L-R-L-R-L-R-L-R-L-cWW-L-L-R
Group  17, IL_04332.3  has acceptance rules  -8.7788 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.7788 - AlignmentScore) +   3.0000 * CoreEdit <=  22.5105, method  8,TP   100.00%, TN    97.93%, min    97.93%,   2 3D sequences,     0 alignment sequences,   338 random sequences,    7 random matches, 13 NTs, cWW-L-R-L-cWW-L-L-R-L-R-L
Group  18, IL_04346.10 has acceptance rules  -7.9350 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.9350 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.50%, min    97.50%,  15 3D sequences,     0 alignment sequences,  1001 random sequences,   25 random matches, 15 NTs, cWW-cWW-tSH-tHH-cSH-tWH-tHS-cWW
Group  19, IL_04600.1  has acceptance rules  -8.6710 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.6710 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.09%, min    97.09%,   1 3D sequences,     0 alignment sequences,  1342 random sequences,   39 random matches, 14 NTs, cWW-cWW-L-R-L-R-L-R-cWW-cWW
Group  20, IL_04638.3  has acceptance rules  -8.8971 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.8971 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    96.32%, min    96.32%,   5 3D sequences,     0 alignment sequences,  2633 random sequences,   97 random matches, 13 NTs, cWW-tSH-tHW-tHS-cSH-cWW-L
Group  21, IL_04650.2  has acceptance rules  -5.4994 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.4994 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.59%, min    97.59%,   4 3D sequences,     0 alignment sequences,  1703 random sequences,   41 random matches, 11 NTs, cWW-cWW-L-cWW-L-R-L-L-cSH
Group  22, IL_04736.1  has acceptance rules  -8.3327 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.3327 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.41%, min    97.41%,   1 3D sequences,     0 alignment sequences,  2204 random sequences,   57 random matches, 12 NTs, cWW-L-R-L-R-L-R-L-R-cWW
Group  23, IL_04785.1  has acceptance rules  -6.7283 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.7283 - AlignmentScore) +   3.0000 * CoreEdit <=  10.7478, method  6,TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences,  9578 random sequences,  383 random matches,  8 NTs, cWW-L-R-L-R-cWW
Group  24, IL_05192.4  has acceptance rules  -9.0486 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.0486 - AlignmentScore) +   3.0000 * CoreEdit <=  13.7605, method  6,TP   100.00%, TN    95.99%, min    95.99%,   3 3D sequences,     0 alignment sequences, 18619 random sequences,  746 random matches, 10 NTs, cWW-L-R-L-R-L-cWW-L
Group  25, IL_05472.1  has acceptance rules  -9.6565 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.6565 - AlignmentScore) +   3.0000 * CoreEdit <=  19.3937, method  6,TP   100.00%, TN    96.77%, min    96.77%,   1 3D sequences,     0 alignment sequences,    62 random sequences,    2 random matches, 14 NTs, cWW-L-R-L-R-L-R-L-R-L-cWW-L
Group  26, IL_06029.1  has acceptance rules -15.4384 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-15.4384 - AlignmentScore) +   3.0000 * CoreEdit <=  25.0000, method  1,TP   100.00%, TN   100.00%, min   100.00%,   1 3D sequences,     0 alignment sequences,     1 random sequences,    0 random matches, 17 NTs, cWW-L-R-L-R-L-cWW-L-L-R-L-R-L-R-L
Group  27, IL_06136.2  has acceptance rules  -9.5549 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.5549 - AlignmentScore) +   3.0000 * CoreEdit <=  14.5059, method  6,TP   100.00%, TN    96.01%, min    96.01%,   6 3D sequences,     0 alignment sequences,  4111 random sequences,  164 random matches, 12 NTs, cWW-tHS-cWW-tHS-tSH-tSH-cWW
Group  28, IL_06300.1  has acceptance rules  -5.5781 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.5781 - AlignmentScore) +   3.0000 * CoreEdit <=  13.8658, method  6,TP   100.00%, TN    95.98%, min    95.98%,   1 3D sequences,     0 alignment sequences, 10786 random sequences,  434 random matches,  9 NTs, cWW-L-R-L-R-L-cWW
Group  29, IL_06549.2  has acceptance rules  -6.0151 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.0151 - AlignmentScore) +   3.0000 * CoreEdit <=  10.2984, method  6,TP   100.00%, TN    96.00%, min    96.00%,   6 3D sequences,     0 alignment sequences, 12437 random sequences,  497 random matches,  4 NTs, cWW-cWW
Group  30, IL_06691.1  has acceptance rules  -6.0145 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.0145 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.09%, min    97.09%,   2 3D sequences,     0 alignment sequences,  3605 random sequences,  105 random matches, 10 NTs, cWW-cWS-L-R-L-R-cWW-L
Group  31, IL_07039.3  has acceptance rules  -3.1610 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.1610 - AlignmentScore) +   3.0000 * CoreEdit <=  12.0942, method  6,TP   100.00%, TN    95.99%, min    95.99%,  16 3D sequences,     0 alignment sequences,  3993 random sequences,  160 random matches,  5 NTs, cWW-L-cWW
Group  32, IL_07171.1  has acceptance rules  -4.8363 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.8363 - AlignmentScore) +   3.0000 * CoreEdit <=  10.4977, method  6,TP   100.00%, TN    95.71%, min    95.71%,   1 3D sequences,     0 alignment sequences, 11991 random sequences,  514 random matches,  6 NTs, cWW-L-cWW-L
Group  33, IL_07173.1  has acceptance rules  -6.2247 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.2247 - AlignmentScore) +   3.0000 * CoreEdit <=  14.8736, method  6,TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences, 17213 random sequences,  690 random matches,  8 NTs, cWW-L-R-L-cWW-L
Group  34, IL_07469.2  has acceptance rules  -3.5301 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.5301 - AlignmentScore) +   3.0000 * CoreEdit <=  18.6881, method  6,TP   100.00%, TN    96.00%, min    96.00%,   3 3D sequences,     0 alignment sequences,  2250 random sequences,   90 random matches, 10 NTs, cWW-tSH-cWW-cSH-R-cWW
Group  35, IL_07785.1  has acceptance rules  -5.1354 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.1354 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    87.46%, min    87.46%,  33 3D sequences,     0 alignment sequences, 11195 random sequences, 1404 random matches,  6 NTs, cWW-cWW-cWW
Group  36, IL_08770.1  has acceptance rules  -6.0197 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.0197 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    82.49%, min    82.49%,   5 3D sequences,     0 alignment sequences, 12784 random sequences, 2238 random matches,  6 NTs, cWW-L-R-cWW
Group  37, IL_09044.1  has acceptance rules  -6.4802 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.4802 - AlignmentScore) +   3.0000 * CoreEdit <=  18.2547, method  6,TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences,  5543 random sequences,  222 random matches, 11 NTs, cWW-tSH-tHH-L-tHS-cWW
Group  38, IL_09129.2  has acceptance rules  -7.8645 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.8645 - AlignmentScore) +   3.0000 * CoreEdit <=  19.8909, method  6,TP   100.00%, TN    96.02%, min    96.02%,   2 3D sequences,     0 alignment sequences,  1860 random sequences,   74 random matches, 14 NTs, cWW-L-R-tWH-L-R-L-tWW-cWW
Group  39, IL_09570.1  has acceptance rules  -8.7071 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.7071 - AlignmentScore) +   3.0000 * CoreEdit <=  19.8960, method  6,TP   100.00%, TN    95.93%, min    95.93%,   1 3D sequences,     0 alignment sequences,  5722 random sequences,  233 random matches, 12 NTs, cWW-L-R-L-R-L-cWW-L-L-R
Group  40, IL_09705.15 has acceptance rules  -5.0731 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.0731 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    95.71%, min    95.71%,  34 3D sequences,     0 alignment sequences,  7745 random sequences,  332 random matches,  8 NTs, cWW-tSH-tHS-cWW
Group  41, IL_09908.1  has acceptance rules  -8.0125 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.0125 - AlignmentScore) +   3.0000 * CoreEdit <=  16.3943, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences,  9976 random sequences,  399 random matches, 11 NTs, cWW-L-tHH-L-R-L-cWW-L
Group  42, IL_09990.4  has acceptance rules  -4.4480 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.4480 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    95.57%, min    95.57%,   2 3D sequences,     0 alignment sequences,  8140 random sequences,  361 random matches,  7 NTs, cWW-L-R-L-cWW
Group  43, IL_10167.6  has acceptance rules  -2.9779 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -2.9779 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP    98.04%, TN    89.55%, min    89.55%,  51 3D sequences,     0 alignment sequences,  4974 random sequences,  520 random matches,  6 NTs, cWW-cHW-cWW
Group  44, IL_10389.1  has acceptance rules  -6.9051 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.9051 - AlignmentScore) +   3.0000 * CoreEdit <=  11.6409, method  6,TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 15894 random sequences,  636 random matches,  8 NTs, cWW-L-cWW-L-cWW
Group  45, IL_10484.1  has acceptance rules  -5.9368 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.9368 - AlignmentScore) +   3.0000 * CoreEdit <=  11.5427, method  6,TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences,  7853 random sequences,  314 random matches,  8 NTs, cWW-tSH-tHS-cWW
Group  46, IL_10569.1  has acceptance rules  -3.5532 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.5532 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    82.30%, min    82.30%,   2 3D sequences,     0 alignment sequences,  6067 random sequences, 1074 random matches,  5 NTs, cWW-L-cWW
Group  47, IL_10796.1  has acceptance rules  -3.5911 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.5911 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    95.64%, min    95.64%,   1 3D sequences,     0 alignment sequences,  6130 random sequences,  267 random matches,  6 NTs, cWW-L-R-cWW
Group  48, IL_11344.2  has acceptance rules  -8.4085 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.4085 - AlignmentScore) +   3.0000 * CoreEdit <=  12.9213, method  6,TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 18726 random sequences,  749 random matches,  5 NTs, cWW-cSS-L-cWW
Group  49, IL_11399.2  has acceptance rules  -4.7105 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.7105 - AlignmentScore) +   3.0000 * CoreEdit <=  13.0760, method  6,TP   100.00%, TN    95.99%, min    95.99%,   3 3D sequences,     0 alignment sequences, 10345 random sequences,  415 random matches,  9 NTs, cWW-cHW-L-R-L-cWW
Group  50, IL_11415.1  has acceptance rules  -4.5092 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.5092 - AlignmentScore) +   3.0000 * CoreEdit <=  15.2748, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 10572 random sequences,  423 random matches,  8 NTs, cWW-L-R-L-cWW-L
Group  51, IL_12566.4  has acceptance rules  -3.8264 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.8264 - AlignmentScore) +   3.0000 * CoreEdit <=  14.5158, method  6,TP   100.00%, TN    96.00%, min    96.00%,   5 3D sequences,     0 alignment sequences,  9828 random sequences,  393 random matches,  9 NTs, cWW-L-tHS-L-cWW-L
Group  52, IL_12697.1  has acceptance rules  -7.9241 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.9241 - AlignmentScore) +   3.0000 * CoreEdit <=  15.7870, method  6,TP   100.00%, TN    95.99%, min    95.99%,   2 3D sequences,     0 alignment sequences,  6939 random sequences,  278 random matches, 10 NTs, cWW-cWW-L-R-tHS-cWW
Group  53, IL_12745.1  has acceptance rules  -6.7221 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.7221 - AlignmentScore) +   3.0000 * CoreEdit <=  20.4151, method  8,TP   100.00%, TN    97.99%, min    97.99%,   1 3D sequences,     0 alignment sequences,  2036 random sequences,   41 random matches, 12 NTs, cWW-tWH-tWH-tHW-tHW-cWW
Group  54, IL_13358.1  has acceptance rules  -8.9956 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.9956 - AlignmentScore) +   3.0000 * CoreEdit <=  21.3834, method  8,TP   100.00%, TN    97.99%, min    97.99%,   1 3D sequences,     0 alignment sequences,   548 random sequences,   11 random matches, 13 NTs, cWW-L-R-L-R-L-R-L-cWW-L-L
Group  55, IL_13394.1  has acceptance rules -16.4920 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-16.4920 - AlignmentScore) +   3.0000 * CoreEdit <=  25.0000, method 12,TP   100.00%, TN      NaN%, min   100.00%,   1 3D sequences,     0 alignment sequences,     0 random sequences,    0 random matches, 21 NTs, cWW-L-R-L-R-L-R-L-R-L-R-L-R-L-R-L-R-L-R-L-R
Group  56, IL_13404.2  has acceptance rules  -4.2188 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.2188 - AlignmentScore) +   3.0000 * CoreEdit <=  12.7311, method  6,TP   100.00%, TN    96.00%, min    96.00%,  10 3D sequences,     0 alignment sequences,  5555 random sequences,  222 random matches,  8 NTs, cWW-cWW-cWW-cWW
Group  57, IL_13874.1  has acceptance rules  -5.8499 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.8499 - AlignmentScore) +   3.0000 * CoreEdit <=  22.4160, method  8,TP   100.00%, TN    98.09%, min    98.09%,   1 3D sequences,     0 alignment sequences,   523 random sequences,   10 random matches, 12 NTs, cWW-cWH-tHS-cWW-cSH-cWH-cHW-cWW
Group  58, IL_14177.2  has acceptance rules  -5.3143 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.3143 - AlignmentScore) +   3.0000 * CoreEdit <=  13.9988, method  6,TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 16959 random sequences,  678 random matches,  7 NTs, cWW-L-R-L-cWW
Group  59, IL_14368.1  has acceptance rules  -2.4141 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -2.4141 - AlignmentScore) +   3.0000 * CoreEdit <=  10.4374, method  6,TP   100.00%, TN    95.98%, min    95.98%,   6 3D sequences,     0 alignment sequences,  8260 random sequences,  332 random matches,  6 NTs, cWW-L-cWW-cSH
Group  60, IL_14688.1  has acceptance rules  -5.9729 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.9729 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    85.72%, min    85.72%,   5 3D sequences,     0 alignment sequences, 10496 random sequences, 1499 random matches,  6 NTs, cWW-cWW-cWW
Group  61, IL_15052.4  has acceptance rules  -4.0784 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.0784 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    90.02%, min    90.02%,   8 3D sequences,     0 alignment sequences,  7382 random sequences,  737 random matches,  6 NTs, cWW-L-cWW-L
Group  62, IL_15107.1  has acceptance rules -13.5141 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-13.5141 - AlignmentScore) +   3.0000 * CoreEdit <=  25.0000, method  1,TP   100.00%, TN   100.00%, min   100.00%,   1 3D sequences,     0 alignment sequences,     5 random sequences,    0 random matches, 18 NTs, cWW-R-L-R-L-R-L-R-L-R-L-R-L-L-L-cWW
Group  63, IL_15218.1  has acceptance rules -10.3814 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-10.3814 - AlignmentScore) +   3.0000 * CoreEdit <=  17.7441, method  6,TP   100.00%, TN    95.99%, min    95.99%,   2 3D sequences,     0 alignment sequences,  5040 random sequences,  202 random matches, 13 NTs, cWW-L-cWW-L-L-R-L-R-L-R-L
Group  64, IL_15698.3  has acceptance rules  -4.4830 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.4830 - AlignmentScore) +   3.0000 * CoreEdit <=  10.2492, method  6,TP   100.00%, TN    96.00%, min    96.00%,  10 3D sequences,     0 alignment sequences, 10495 random sequences,  420 random matches,  7 NTs, cWW-L-R-L-cWW
Group  65, IL_15991.1  has acceptance rules -16.4481 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-16.4481 - AlignmentScore) +   3.0000 * CoreEdit <=  25.0000, method 12,TP   100.00%, TN      NaN%, min   100.00%,   1 3D sequences,     0 alignment sequences,     0 random sequences,    0 random matches, 21 NTs, cWW-L-R-L-R-L-R-L-R-L-R-L-R-L-R-L-cWW-L-L
Group  66, IL_16218.2  has acceptance rules  -6.3399 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.3399 - AlignmentScore) +   3.0000 * CoreEdit <=  14.9630, method  6,TP   100.00%, TN    96.00%, min    96.00%,   3 3D sequences,     0 alignment sequences, 10494 random sequences,  420 random matches,  9 NTs, cWW-L-R-L-R-L-cWW
Group  67, IL_16386.4  has acceptance rules  -3.1313 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.1313 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    86.54%, min    86.54%,   4 3D sequences,     0 alignment sequences,  4628 random sequences,  623 random matches,  5 NTs, cWW-L-cWW
Group  68, IL_16458.4  has acceptance rules  -4.5673 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.5673 - AlignmentScore) +   3.0000 * CoreEdit <=  21.2634, method  8,TP   100.00%, TN    98.00%, min    98.00%,   5 3D sequences,     0 alignment sequences,  1553 random sequences,   31 random matches, 13 NTs, cWW-L-R-L-R-cSH-tWH-tHS-cWW
Group  69, IL_16665.1  has acceptance rules -10.3767 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-10.3767 - AlignmentScore) +   3.0000 * CoreEdit <=  18.6637, method  6,TP   100.00%, TN    95.78%, min    95.78%,   1 3D sequences,     0 alignment sequences,  1871 random sequences,   79 random matches, 11 NTs, cWW-L-R-L-R-L-R-L-cWW
Group  70, IL_17069.5  has acceptance rules  -7.7917 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.7917 - AlignmentScore) +   3.0000 * CoreEdit <=  22.7794, method  8,TP   100.00%, TN    97.96%, min    97.96%,   5 3D sequences,     0 alignment sequences,   783 random sequences,   16 random matches, 13 NTs, cWW-tSH-tHH-cSS-tWW-tHH-tSS-cWW
Group  71, IL_17136.7  has acceptance rules  -6.0194 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.0194 - AlignmentScore) +   3.0000 * CoreEdit <=  11.3587, method  6,TP   100.00%, TN    95.99%, min    95.99%,  14 3D sequences,     0 alignment sequences,  4669 random sequences,  187 random matches, 10 NTs, cWW-tSH-tHW-tHS-cWW
Group  72, IL_17765.1  has acceptance rules  -8.3880 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.3880 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.01%, min    97.01%,   1 3D sequences,     0 alignment sequences,   569 random sequences,   17 random matches, 14 NTs, cWW-tWH-cHW-L-tSS-cSS-cWW-R-L
Group  73, IL_17948.2  has acceptance rules  -6.4166 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.4166 - AlignmentScore) +   3.0000 * CoreEdit <=  11.9363, method  6,TP   100.00%, TN    96.00%, min    96.00%,  13 3D sequences,     0 alignment sequences,  5779 random sequences,  231 random matches, 10 NTs, cWW-L-R-tSH-tHS-cWW
Group  74, IL_17973.1  has acceptance rules -14.1073 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-14.1073 - AlignmentScore) +   3.0000 * CoreEdit <=  25.0000, method  1,TP   100.00%, TN   100.00%, min   100.00%,   1 3D sequences,     0 alignment sequences,     1 random sequences,    0 random matches, 18 NTs, cWW-cWW-L-cWW-L-L-R-L-R-L-R-L-R-L-R
Group  75, IL_18354.1  has acceptance rules -10.7345 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-10.7345 - AlignmentScore) +   3.0000 * CoreEdit <=  16.2053, method  6,TP   100.00%, TN    95.97%, min    95.97%,   2 3D sequences,     0 alignment sequences,  7028 random sequences,  283 random matches, 12 NTs, cWW-L-cWW-L-L-R-L-R-L-R
Group  76, IL_18472.4  has acceptance rules  -5.4461 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.4461 - AlignmentScore) +   3.0000 * CoreEdit <=  17.3233, method  6,TP   100.00%, TN    96.00%, min    96.00%,   3 3D sequences,     0 alignment sequences,  5204 random sequences,  208 random matches, 11 NTs, cWW-tSW-R-L-R-L-R-cWW
Group  77, IL_18487.1  has acceptance rules  -5.6423 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.6423 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    96.42%, min    96.42%,   2 3D sequences,     0 alignment sequences,  2293 random sequences,   82 random matches, 13 NTs, cWW-L-R-L-R-L-R-L-cWW-cWW
Group  78, IL_19048.1  has acceptance rules  -8.1859 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.1859 - AlignmentScore) +   3.0000 * CoreEdit <=  22.4114, method  8,TP   100.00%, TN    98.08%, min    98.08%,   1 3D sequences,     0 alignment sequences,   261 random sequences,    5 random matches, 14 NTs, cWW-L-R-L-R-L-cSH-L-R-cWW-cWW
Group  79, IL_19102.1  has acceptance rules  -6.3604 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.3604 - AlignmentScore) +   3.0000 * CoreEdit <=  10.2081, method  6,TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 13637 random sequences,  545 random matches,  7 NTs, cWW-L-R-L-cWW
Group  80, IL_19516.1  has acceptance rules -13.3269 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-13.3269 - AlignmentScore) +   3.0000 * CoreEdit <=  25.0000, method  1,TP   100.00%, TN    75.00%, min    75.00%,   1 3D sequences,     0 alignment sequences,    20 random sequences,    5 random matches, 18 NTs, cWW-L-R-L-R-L-cWW-L-cWW-L-L-L-R-L-R
Group  81, IL_19668.1  has acceptance rules  -7.6625 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.6625 - AlignmentScore) +   3.0000 * CoreEdit <=  11.4683, method  6,TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 19666 random sequences,  787 random matches,  8 NTs, cWW-cWW-L-cWW-L
Group  82, IL_19852.1  has acceptance rules  -6.2429 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.2429 - AlignmentScore) +   3.0000 * CoreEdit <=  20.7174, method  8,TP   100.00%, TN    98.01%, min    98.01%,   1 3D sequences,     0 alignment sequences,   957 random sequences,   19 random matches, 11 NTs, cWW-tWH-cWW-cWH-cWH-cWH
Group  83, IL_19897.3  has acceptance rules  -6.0474 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.0474 - AlignmentScore) +   3.0000 * CoreEdit <=  19.2619, method  6,TP   100.00%, TN    95.99%, min    95.99%,   2 3D sequences,     0 alignment sequences,  4766 random sequences,  191 random matches, 11 NTs, cWW-L-cWW-L-L-tWH-R-L
Group  84, IL_20031.1  has acceptance rules  -6.6705 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.6705 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    89.24%, min    89.24%,   2 3D sequences,     0 alignment sequences, 14922 random sequences, 1605 random matches,  6 NTs, cWW-L-cWW-L
Group  85, IL_20047.1  has acceptance rules  -6.5682 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.5682 - AlignmentScore) +   3.0000 * CoreEdit <=  21.0022, method  8,TP   100.00%, TN    97.99%, min    97.99%,   2 3D sequences,     0 alignment sequences,  1489 random sequences,   30 random matches, 11 NTs, cWW-tSH-tWH-cSH-cHW-cWH-cWW-cWW
Group  86, IL_20245.1  has acceptance rules -18.0765 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-18.0765 - AlignmentScore) +   3.0000 * CoreEdit <=  25.0000, method 12,TP   100.00%, TN      NaN%, min   100.00%,   1 3D sequences,     0 alignment sequences,     0 random sequences,    0 random matches, 18 NTs, cWW-L-R-L-R-L-R-L-R-L-R-L-R-L-cWW-L-L-R-L
Group  87, IL_20463.1  has acceptance rules  -9.8739 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.8739 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    96.72%, min    96.72%,   1 3D sequences,     0 alignment sequences,    61 random sequences,    2 random matches, 18 NTs, cWW-tSH-tHW-cSH-tHH-cWH-L-R-cWW-L-L-R
Group  88, IL_21001.1  has acceptance rules  -5.7383 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.7383 - AlignmentScore) +   3.0000 * CoreEdit <=  16.1051, method  6,TP   100.00%, TN    96.00%, min    96.00%,   3 3D sequences,     0 alignment sequences, 10821 random sequences,  433 random matches,  9 NTs, cWW-L-R-tHW-L-cWW
Group  89, IL_21173.1  has acceptance rules  -5.3948 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.3948 - AlignmentScore) +   3.0000 * CoreEdit <=  18.5561, method  6,TP   100.00%, TN    95.79%, min    95.79%,   2 3D sequences,     0 alignment sequences,  5373 random sequences,  226 random matches, 11 NTs, cWW-L-cWW-L-L-R-L-R-L
Group  90, IL_21200.1  has acceptance rules  -6.3201 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.3201 - AlignmentScore) +   3.0000 * CoreEdit <=  14.9926, method  6,TP   100.00%, TN    96.00%, min    96.00%,   6 3D sequences,     0 alignment sequences,  9823 random sequences,  393 random matches, 10 NTs, cWW-tSH-tHW-L-cWW-L
Group  91, IL_21630.1  has acceptance rules -11.6160 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-11.6160 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.76%, min    97.76%,   1 3D sequences,     0 alignment sequences,   223 random sequences,    5 random matches, 17 NTs, cWW-L-R-L-R-L-R-cSH-R-tWH-R-cWW-cWW
Group  92, IL_21667.1  has acceptance rules  -6.8759 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.8759 - AlignmentScore) +   3.0000 * CoreEdit <=  16.2152, method  6,TP   100.00%, TN    95.91%, min    95.91%,   2 3D sequences,     0 alignment sequences,  9023 random sequences,  369 random matches, 11 NTs, cWW-tSH-L-R-L-cWW
Group  93, IL_22373.1  has acceptance rules  -3.5769 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.5769 - AlignmentScore) +   3.0000 * CoreEdit <=  14.3765, method  6,TP   100.00%, TN    95.96%, min    95.96%,   4 3D sequences,     0 alignment sequences,  3665 random sequences,  148 random matches,  8 NTs, cWW-L-R-cSH-cSH-cWW
Group  94, IL_22551.4  has acceptance rules  -3.9495 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.9495 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    87.34%, min    87.34%,   9 3D sequences,     0 alignment sequences,  9075 random sequences, 1149 random matches,  6 NTs, cWW-L-cWW-L
Group  95, IL_22564.1  has acceptance rules  -9.5033 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.5033 - AlignmentScore) +   3.0000 * CoreEdit <=  17.1748, method  6,TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences,  3923 random sequences,  157 random matches,  9 NTs, cWW-L-R-L-R-L-cWW
Group  96, IL_22829.2  has acceptance rules  -6.8665 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.8665 - AlignmentScore) +   3.0000 * CoreEdit <=  17.6592, method  6,TP   100.00%, TN    96.00%, min    96.00%,   3 3D sequences,     0 alignment sequences,  6698 random sequences,  268 random matches, 11 NTs, cWW-L-tHS-L-R-L-cWW-L
Group  97, IL_22854.4  has acceptance rules  -5.2631 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.2631 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.54%, min    97.54%,   7 3D sequences,     0 alignment sequences,   487 random sequences,   12 random matches, 14 NTs, cWW-tSH-cWW-tHW-R-L-cWW-L-L-R
Group  98, IL_23038.1  has acceptance rules  -5.0164 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.0164 - AlignmentScore) +   3.0000 * CoreEdit <=  21.9671, method  8,TP   100.00%, TN    98.00%, min    98.00%,   2 3D sequences,     0 alignment sequences,   449 random sequences,    9 random matches, 13 NTs, cWW-L-R-tWH-L-R-L-cWW-cWW
Group  99, IL_23774.1  has acceptance rules  -7.8605 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.8605 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    95.12%, min    95.12%,  11 3D sequences,     0 alignment sequences, 10305 random sequences,  503 random matches,  9 NTs, cWW-L-R-L-tHS-cWW
Group 100, IL_24134.1  has acceptance rules  -4.2755 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.2755 - AlignmentScore) +   3.0000 * CoreEdit <=  16.1836, method  6,TP   100.00%, TN    95.71%, min    95.71%,   3 3D sequences,     0 alignment sequences,  1374 random sequences,   59 random matches, 12 NTs, cWW-tSS-L-R-L-tHS-L-cWW-L-L
Group 101, IL_24254.1  has acceptance rules  -5.5592 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.5592 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.86%, min    97.86%,   1 3D sequences,     0 alignment sequences,  1404 random sequences,   30 random matches, 13 NTs, cWW-cWW-tHH-cSH-tWH-tHS-cWW
Group 102, IL_24499.1  has acceptance rules  -7.4797 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.4797 - AlignmentScore) +   3.0000 * CoreEdit <=  18.6173, method  6,TP   100.00%, TN    96.01%, min    96.01%,   1 3D sequences,     0 alignment sequences,  4512 random sequences,  180 random matches, 12 NTs, cWW-cWS-L-R-L-R-cWW-L-cSH-L
Group 103, IL_25186.4  has acceptance rules  -5.7388 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.7388 - AlignmentScore) +   3.0000 * CoreEdit <=  18.5048, method  6,TP   100.00%, TN    96.00%, min    96.00%,   6 3D sequences,     0 alignment sequences,  9243 random sequences,  370 random matches, 10 NTs, cWW-L-R-L-R-L-R-cWW
Group 104, IL_25412.1  has acceptance rules  -5.2890 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.2890 - AlignmentScore) +   3.0000 * CoreEdit <=  15.2246, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 10711 random sequences,  428 random matches,  7 NTs, cWW-L-cWW-L-L
Group 105, IL_25463.1  has acceptance rules  -7.6856 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.6856 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    94.40%, min    94.40%,   2 3D sequences,     0 alignment sequences, 19369 random sequences, 1085 random matches,  7 NTs, cWW-L-cWW-L-L
Group 106, IL_25573.1  has acceptance rules  -3.6057 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.6057 - AlignmentScore) +   3.0000 * CoreEdit <=  13.9053, method  6,TP   100.00%, TN    95.89%, min    95.89%,   1 3D sequences,     0 alignment sequences,  6299 random sequences,  259 random matches,  8 NTs, cWW-tSW-L-cWW-L-L
Group 107, IL_25872.4  has acceptance rules  -6.0035 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.0035 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    94.57%, min    94.57%,   5 3D sequences,     0 alignment sequences,  7887 random sequences,  428 random matches,  8 NTs, cWW-cWW-cWH-cWW
Group 108, IL_26222.2  has acceptance rules  -2.1973 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -2.1973 - AlignmentScore) +   3.0000 * CoreEdit <=  15.3158, method  6,TP   100.00%, TN    95.95%, min    95.95%,   6 3D sequences,     0 alignment sequences,  2100 random sequences,   85 random matches,  9 NTs, cWW-cWS-cSH-tWH-R-L-R-cWW
Group 109, IL_26307.2  has acceptance rules  -7.6895 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.6895 - AlignmentScore) +   3.0000 * CoreEdit <=  18.8396, method  6,TP   100.00%, TN    96.01%, min    96.01%,   9 3D sequences,     0 alignment sequences,  2554 random sequences,  102 random matches, 13 NTs, cWW-tSH-tHH-cSH-tWH-tHS-cWW
Group 110, IL_26598.1  has acceptance rules  -5.4565 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.4565 - AlignmentScore) +   3.0000 * CoreEdit <=  15.8017, method  6,TP   100.00%, TN    96.00%, min    96.00%,   5 3D sequences,     0 alignment sequences,  7047 random sequences,  282 random matches, 10 NTs, cWW-L-cWW-L-L-R-L-R
Group 111, IL_26685.1  has acceptance rules  -3.7358 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.7358 - AlignmentScore) +   3.0000 * CoreEdit <=  11.6667, method  6,TP   100.00%, TN    95.92%, min    95.92%,   1 3D sequences,     0 alignment sequences,  9512 random sequences,  388 random matches,  6 NTs, cWW-L-cWW-L
Group 112, IL_26728.3  has acceptance rules  -5.1475 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.1475 - AlignmentScore) +   3.0000 * CoreEdit <=  17.4591, method  6,TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences,  4845 random sequences,  194 random matches,  9 NTs, cWW-cSH-R-cSH-cWW-cWW
Group 113, IL_26793.1  has acceptance rules  -3.4310 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.4310 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    91.83%, min    91.83%,  16 3D sequences,     0 alignment sequences,  4356 random sequences,  356 random matches,  5 NTs, cWW-L-cWW
Group 114, IL_27393.10 has acceptance rules  -5.4427 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.4427 - AlignmentScore) +   3.0000 * CoreEdit <=  17.3164, method  6,TP   100.00%, TN    95.98%, min    95.98%,   3 3D sequences,     0 alignment sequences,  7208 random sequences,  290 random matches, 10 NTs, cWW-L-cWW-L-L-R-L-R
Group 115, IL_28026.3  has acceptance rules  -6.5426 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.5426 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.83%, min    97.83%,   2 3D sequences,     0 alignment sequences,   276 random sequences,    6 random matches, 15 NTs, cWW-tSH-tWH-cWH-L-tHW-tSS-tHH-cWW
Group 116, IL_28037.2  has acceptance rules  -2.7996 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -2.7996 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    89.89%, min    89.89%,  65 3D sequences,     0 alignment sequences,  4421 random sequences,  447 random matches,  6 NTs, cWW-cWW-cWW
Group 117, IL_28304.1  has acceptance rules -10.5071 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-10.5071 - AlignmentScore) +   3.0000 * CoreEdit <=  20.9971, method  8,TP   100.00%, TN    98.44%, min    98.44%,   1 3D sequences,     0 alignment sequences,    64 random sequences,    1 random matches, 16 NTs, cWW-R-L-R-L-R-L-R-L-L-L-cWW-cWW
Group 118, IL_28564.1  has acceptance rules  -4.7743 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.7743 - AlignmentScore) +   3.0000 * CoreEdit <=  12.3726, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences,  9347 random sequences,  374 random matches,  7 NTs, cWW-L-R-L-cWW
Group 119, IL_28788.1  has acceptance rules  -5.6470 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.6470 - AlignmentScore) +   3.0000 * CoreEdit <=  10.8672, method  6,TP   100.00%, TN    95.84%, min    95.84%,   1 3D sequences,     0 alignment sequences, 15807 random sequences,  657 random matches,  6 NTs, cWW-L-R-cWW
Group 120, IL_29198.2  has acceptance rules  -7.5051 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.5051 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    96.71%, min    96.71%,   4 3D sequences,     0 alignment sequences,  1852 random sequences,   61 random matches, 14 NTs, cWW-cWW-L-R-cSH-R-tWH-tHS-cWW
Group 121, IL_29223.1  has acceptance rules  -6.2659 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.2659 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    96.46%, min    96.46%,   2 3D sequences,     0 alignment sequences,  3562 random sequences,  126 random matches, 11 NTs, cWW-L-R-L-cWW-cWW-cWW
Group 122, IL_29346.2  has acceptance rules  -4.3837 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.3837 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    95.61%, min    95.61%,   3 3D sequences,     0 alignment sequences, 12369 random sequences,  543 random matches,  7 NTs, cWW-L-cWW-L-L
Group 123, IL_29357.1  has acceptance rules  -7.9155 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.9155 - AlignmentScore) +   3.0000 * CoreEdit <=  25.0000, method  1,TP   100.00%, TN   100.00%, min   100.00%,   1 3D sequences,     0 alignment sequences,     1 random sequences,    0 random matches, 18 NTs, cWW-L-R-L-R-cWH-tHW-cSH-cWW-L-L-cWW-R-R
Group 124, IL_29471.1  has acceptance rules  -6.2861 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.2861 - AlignmentScore) +   3.0000 * CoreEdit <=  16.0309, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 10685 random sequences,  427 random matches, 10 NTs, cWW-cWW-L-tHS-L-cWW
Group 125, IL_29826.1  has acceptance rules -18.0383 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-18.0383 - AlignmentScore) +   3.0000 * CoreEdit <=  25.0000, method 12,TP   100.00%, TN      NaN%, min   100.00%,   1 3D sequences,     0 alignment sequences,     0 random sequences,    0 random matches, 25 NTs, cWW-tSH-tHH-L-R-L-R-cSH-R-R-L-R-L-R-L-R-L-R-L-cWW
Group 126, IL_30441.1  has acceptance rules -10.9663 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-10.9663 - AlignmentScore) +   3.0000 * CoreEdit <=  19.7126, method  6,TP   100.00%, TN    95.61%, min    95.61%,   1 3D sequences,     0 alignment sequences,   114 random sequences,    5 random matches, 14 NTs, cWW-cSH-tSW-tHW-cWW-L-L-R-L-L-R
Group 127, IL_30730.1  has acceptance rules  -5.8665 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.8665 - AlignmentScore) +   3.0000 * CoreEdit <=  20.2949, method  8,TP   100.00%, TN    98.02%, min    98.02%,   2 3D sequences,     0 alignment sequences,  2274 random sequences,   45 random matches,  9 NTs, cWW-cSH-L-R-L-cWW-L-R
Group 128, IL_31084.1  has acceptance rules  -8.2173 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.2173 - AlignmentScore) +   3.0000 * CoreEdit <=  17.2726, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences,  7319 random sequences,  293 random matches, 12 NTs, cWW-L-R-L-R-L-R-L-cWW-L
Group 129, IL_31462.6  has acceptance rules  -2.2676 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -2.2676 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    90.52%, min    90.52%, 130 3D sequences,     0 alignment sequences,  4166 random sequences,  395 random matches,  5 NTs, cWW-L-cWW
Group 130, IL_31504.1  has acceptance rules  -9.5589 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.5589 - AlignmentScore) +   3.0000 * CoreEdit <=  25.0000, method  1,TP   100.00%, TN    90.91%, min    90.91%,   1 3D sequences,     0 alignment sequences,    11 random sequences,    1 random matches, 18 NTs, cWW-cWW-cWS-tSH-L-tWH-cWW-tSS-tSH-L-R-L
Group 131, IL_31531.3  has acceptance rules  -3.4261 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.4261 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    94.92%, min    94.92%,  13 3D sequences,     0 alignment sequences,  8402 random sequences,  427 random matches,  7 NTs, cWW-L-R-L-cWW
Group 132, IL_31558.1  has acceptance rules  -5.7275 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.7275 - AlignmentScore) +   3.0000 * CoreEdit <=  13.8579, method  6,TP   100.00%, TN    95.95%, min    95.95%,   1 3D sequences,     0 alignment sequences, 11098 random sequences,  449 random matches,  9 NTs, cWW-L-tHS-L-R-cWW
Group 133, IL_31561.1  has acceptance rules  -5.5778 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.5778 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.62%, min    97.62%,   1 3D sequences,     0 alignment sequences,  2650 random sequences,   63 random matches, 13 NTs, cWW-L-R-tWH-tWH-L-R-L-cWW
Group 134, IL_31737.3  has acceptance rules  -4.8320 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.8320 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    80.57%, min    80.57%,  12 3D sequences,     0 alignment sequences, 10284 random sequences, 1998 random matches,  5 NTs, cWW-L-cWW
Group 135, IL_31915.1  has acceptance rules  -8.5073 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.5073 - AlignmentScore) +   3.0000 * CoreEdit <=  21.1643, method  8,TP   100.00%, TN    97.89%, min    97.89%,   3 3D sequences,     0 alignment sequences,   190 random sequences,    4 random matches, 15 NTs, cWW-L-R-L-R-L-R-L-R-L-R-L-cWW
Group 136, IL_32016.1  has acceptance rules  -6.1551 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.1551 - AlignmentScore) +   3.0000 * CoreEdit <=  19.3910, method  6,TP   100.00%, TN    95.98%, min    95.98%,   1 3D sequences,     0 alignment sequences,  1791 random sequences,   72 random matches, 12 NTs, cWW-tSH-tSH-tSS-tHS-L-R-cWW
Group 137, IL_32056.1  has acceptance rules  -6.5574 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.5574 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.33%, min    97.33%,   3 3D sequences,     0 alignment sequences,  1907 random sequences,   51 random matches, 13 NTs, cWW-L-cWW-L-L-tWH-R-L-R-L
Group 138, IL_33141.1  has acceptance rules  -7.0559 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.0559 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    96.68%, min    96.68%,   1 3D sequences,     0 alignment sequences,  4584 random sequences,  152 random matches, 11 NTs, cWW-L-R-L-R-L-cWW-L-L
Group 139, IL_33323.1  has acceptance rules  -6.4717 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.4717 - AlignmentScore) +   3.0000 * CoreEdit <=  13.2361, method  6,TP   100.00%, TN    96.01%, min    96.01%,   2 3D sequences,     0 alignment sequences,  9037 random sequences,  361 random matches,  9 NTs, cWW-L-R-L-cWW-L-L
Group 140, IL_33623.1  has acceptance rules  -7.9288 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.9288 - AlignmentScore) +   3.0000 * CoreEdit <=  19.4461, method  6,TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences,  5363 random sequences,  215 random matches, 12 NTs, cWW-L-tHH-L-R-L-cWW-L-R
Group 141, IL_33711.1  has acceptance rules  -8.0055 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.0055 - AlignmentScore) +   3.0000 * CoreEdit <=  17.4350, method  6,TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences,  7603 random sequences,  304 random matches,  9 NTs, cWW-cSH-cWW-L-L-R-L
Group 142, IL_33761.2  has acceptance rules  -3.7914 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.7914 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    83.67%, min    83.67%,   3 3D sequences,     0 alignment sequences,  8011 random sequences, 1308 random matches,  5 NTs, cWW-L-cWW
Group 143, IL_33886.1  has acceptance rules  -9.9225 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.9225 - AlignmentScore) +   3.0000 * CoreEdit <=  16.6253, method  6,TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences,  8505 random sequences,  340 random matches, 11 NTs, cWW-L-cWW-L-R-L-R-cWW
Group 144, IL_34470.3  has acceptance rules  -8.9642 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.9642 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.71%, min    97.71%,   2 3D sequences,     0 alignment sequences,   175 random sequences,    4 random matches, 17 NTs, cWW-cSH-cWW-tHH-tWH-tHS-cWW-tSH-R-cWW-L
Group 145, IL_34737.1  has acceptance rules  -6.4607 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.4607 - AlignmentScore) +   3.0000 * CoreEdit <=  15.9611, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 14474 random sequences,  579 random matches,  9 NTs, cWW-L-cHW-L-cWW-L
Group 146, IL_34739.3  has acceptance rules -11.3540 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-11.3540 - AlignmentScore) +   3.0000 * CoreEdit <=  25.0000, method 12,TP   100.00%, TN      NaN%, min   100.00%,   3 3D sequences,     0 alignment sequences,     0 random sequences,    0 random matches, 20 NTs, cWW-tWW-tWW-L-R-L-R-L-cWW-L-L-R-L-R-L-R-L-R
Group 147, IL_34822.1  has acceptance rules  -9.4644 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.4644 - AlignmentScore) +   3.0000 * CoreEdit <=  16.8012, method  6,TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences,  5295 random sequences,  212 random matches, 12 NTs, cWW-L-R-L-R-L-R-L-R-cWW
Group 148, IL_36516.3  has acceptance rules  -6.2663 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.2663 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    95.62%, min    95.62%,   7 3D sequences,     0 alignment sequences,  8611 random sequences,  377 random matches,  8 NTs, cWW-cWW-cSH-cWW-L
Group 149, IL_36729.1  has acceptance rules -11.8345 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-11.8345 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    96.96%, min    96.96%,   1 3D sequences,     0 alignment sequences,   230 random sequences,    7 random matches, 17 NTs, cWW-cWW-L-R-L-R-L-R-tWH-R-L-R-L-cWW
Group 150, IL_37015.1  has acceptance rules  -8.3531 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.3531 - AlignmentScore) +   3.0000 * CoreEdit <=  19.2433, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences,  1176 random sequences,   47 random matches, 13 NTs, cWW-tSS-tSS-tHH-L-tHS-L-R-cWW-L
Group 151, IL_37603.1  has acceptance rules  -7.6534 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.6534 - AlignmentScore) +   3.0000 * CoreEdit <=  19.0952, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences,  7580 random sequences,  303 random matches, 10 NTs, cWW-L-cWW-L-cWW-L-L
Group 152, IL_37752.1  has acceptance rules  -7.2318 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.2318 - AlignmentScore) +   3.0000 * CoreEdit <=  24.4725, method  8,TP   100.00%, TN    97.85%, min    97.85%,   1 3D sequences,     0 alignment sequences,   186 random sequences,    4 random matches, 12 NTs, cWW-L-R-L-R-tHW-R-L-cWW
Group 153, IL_38186.6  has acceptance rules  -5.1231 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.1231 - AlignmentScore) +   3.0000 * CoreEdit <=  12.4048, method  6,TP   100.00%, TN    95.96%, min    95.96%,   4 3D sequences,     0 alignment sequences, 10047 random sequences,  406 random matches,  8 NTs, cWW-L-cWW-L-L-R
Group 154, IL_38394.1  has acceptance rules  -5.4278 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.4278 - AlignmentScore) +   3.0000 * CoreEdit <=  15.2382, method  6,TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences,  3828 random sequences,  153 random matches, 10 NTs, cWW-tWH-cWW-L-L-R-L
Group 155, IL_38507.2  has acceptance rules  -5.0903 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.0903 - AlignmentScore) +   3.0000 * CoreEdit <=  12.2995, method  6,TP   100.00%, TN    96.00%, min    96.00%,  16 3D sequences,     0 alignment sequences,  8266 random sequences,  331 random matches,  9 NTs, cWW-tWH-L-tHS-cWW
Group 156, IL_38634.5  has acceptance rules  -7.2389 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.2389 - AlignmentScore) +   3.0000 * CoreEdit <=  13.0206, method  6,TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 10876 random sequences,  435 random matches,  8 NTs, cWW-cWH-L-R-cWW
Group 157, IL_38862.4  has acceptance rules  -6.0319 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.0319 - AlignmentScore) +   3.0000 * CoreEdit <=  11.1957, method  6,TP   100.00%, TN    95.99%, min    95.99%,   5 3D sequences,     0 alignment sequences,  3590 random sequences,  144 random matches, 10 NTs, cWW-cSH-R-tWH-tHS-cWW
Group 158, IL_38969.1  has acceptance rules  -8.3902 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.3902 - AlignmentScore) +   3.0000 * CoreEdit <=  18.2700, method  6,TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences,  2544 random sequences,  102 random matches,  9 NTs, cWW-L-R-L-cWW-L-L
Group 159, IL_41203.4  has acceptance rules  -6.6751 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.6751 - AlignmentScore) +   3.0000 * CoreEdit <=  13.8343, method  6,TP   100.00%, TN    96.00%, min    96.00%,  11 3D sequences,     0 alignment sequences,  6645 random sequences,  266 random matches, 10 NTs, cWW-L-cWW-L-L-R-cSH
Group 160, IL_41344.1  has acceptance rules  -7.0024 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.0024 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    89.87%, min    89.87%,   2 3D sequences,     0 alignment sequences, 11370 random sequences, 1152 random matches,  7 NTs, cWW-L-R-L-cWW
Group 161, IL_41756.4  has acceptance rules  -6.8896 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.8896 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.55%, min    97.55%,   4 3D sequences,     0 alignment sequences,  1225 random sequences,   30 random matches, 14 NTs, cWW-tSH-tHH-cSH-tWH-tHS-cWW-L
Group 162, IL_41853.1  has acceptance rules -10.1591 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-10.1591 - AlignmentScore) +   3.0000 * CoreEdit <=  18.1969, method  6,TP   100.00%, TN    96.01%, min    96.01%,   1 3D sequences,     0 alignment sequences,  5535 random sequences,  221 random matches, 13 NTs, cWW-L-tHH-L-tHS-L-cWW-L-L
Group 163, IL_42032.1  has acceptance rules  -4.7916 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.7916 - AlignmentScore) +   3.0000 * CoreEdit <=  18.4111, method  6,TP   100.00%, TN    95.97%, min    95.97%,   2 3D sequences,     0 alignment sequences,  1838 random sequences,   74 random matches, 11 NTs, cWW-cSH-cWW-tWH-L-cWW-L-L
Group 164, IL_42218.2  has acceptance rules  -8.1750 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.1750 - AlignmentScore) +   3.0000 * CoreEdit <=  20.5974, method  8,TP   100.00%, TN    98.14%, min    98.14%,   5 3D sequences,     0 alignment sequences,   215 random sequences,    4 random matches, 13 NTs, cWW-L-R-cHW-cWW-L-L-L-R-L
Group 165, IL_42231.1  has acceptance rules -10.7332 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-10.7332 - AlignmentScore) +   3.0000 * CoreEdit <=  20.9068, method  8,TP   100.00%, TN    98.05%, min    98.05%,   2 3D sequences,     0 alignment sequences,   615 random sequences,   12 random matches, 12 NTs, cWW-L-R-L-cWW-L-cWW-cSS-L
Group 166, IL_42314.1  has acceptance rules  -5.7576 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.7576 - AlignmentScore) +   3.0000 * CoreEdit <=  11.8925, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 13587 random sequences,  543 random matches,  7 NTs, cWW-L-R-L-cWW
Group 167, IL_42626.2  has acceptance rules  -4.8482 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.8482 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    82.64%, min    82.64%,  14 3D sequences,     0 alignment sequences,  8941 random sequences, 1552 random matches,  4 NTs, cWW-cWW
Group 168, IL_42771.1  has acceptance rules  -4.5079 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.5079 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    76.59%, min    76.59%,   6 3D sequences,     0 alignment sequences,  7060 random sequences, 1653 random matches,  4 NTs, cWW-cWW
Group 169, IL_42778.1  has acceptance rules  -8.7794 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.7794 - AlignmentScore) +   3.0000 * CoreEdit <=  17.6814, method  6,TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences,  6579 random sequences,  264 random matches, 11 NTs, cWW-L-R-L-R-L-R-L-cWW
Group 170, IL_42997.3  has acceptance rules  -4.4671 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.4671 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    84.48%, min    84.48%,  20 3D sequences,     0 alignment sequences,  6644 random sequences, 1031 random matches,  6 NTs, cWW-L-R-cWW
Group 171, IL_43140.1  has acceptance rules  -7.2894 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.2894 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    96.82%, min    96.82%,   1 3D sequences,     0 alignment sequences,  2329 random sequences,   74 random matches,  9 NTs, cWW-L-cWW-cWH-L-L
Group 172, IL_43467.1  has acceptance rules -12.2918 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-12.2918 - AlignmentScore) +   3.0000 * CoreEdit <=  22.0175, method  8,TP   100.00%, TN    96.77%, min    96.77%,   1 3D sequences,     0 alignment sequences,    31 random sequences,    1 random matches, 17 NTs, cWW-L-R-L-R-L-R-L-R-L-cWW-L-L-R-L
Group 173, IL_43547.1  has acceptance rules  -8.2272 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.2272 - AlignmentScore) +   3.0000 * CoreEdit <=  21.9415, method  8,TP   100.00%, TN    97.62%, min    97.62%,   3 3D sequences,     0 alignment sequences,    84 random sequences,    2 random matches, 18 NTs, cWW-tSH-tHH-cSH-tWH-tHS-R-L-cWW-L-cWW
Group 174, IL_43622.1  has acceptance rules  -4.3379 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.3379 - AlignmentScore) +   3.0000 * CoreEdit <=  15.8148, method  6,TP   100.00%, TN    95.99%, min    95.99%,   2 3D sequences,     0 alignment sequences, 12784 random sequences,  512 random matches,  8 NTs, cWW-cWW-L-cWW-L
Group 175, IL_43644.1  has acceptance rules  -5.6107 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.6107 - AlignmentScore) +   3.0000 * CoreEdit <=  11.1652, method  6,TP   100.00%, TN    95.98%, min    95.98%,   2 3D sequences,     0 alignment sequences,  6142 random sequences,  247 random matches,  8 NTs, cWW-cWW-L-R-cWW
Group 176, IL_43858.1  has acceptance rules  -8.0031 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.0031 - AlignmentScore) +   3.0000 * CoreEdit <=  23.6897, method  8,TP   100.00%, TN    97.47%, min    97.47%,   2 3D sequences,     0 alignment sequences,    79 random sequences,    2 random matches, 15 NTs, cWW-tSH-cSH-tWH-cSH-cHW-cWH-cWW-cWW
Group 177, IL_44325.1  has acceptance rules  -5.8210 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.8210 - AlignmentScore) +   3.0000 * CoreEdit <=  11.0894, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 14695 random sequences,  588 random matches,  6 NTs, cWW-cWH-cWW-L
Group 178, IL_44438.1  has acceptance rules  -7.9246 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.9246 - AlignmentScore) +   3.0000 * CoreEdit <=  18.1709, method  6,TP   100.00%, TN    95.74%, min    95.74%,   1 3D sequences,     0 alignment sequences,  6242 random sequences,  266 random matches, 12 NTs, cWW-L-R-L-R-L-R-L-R-cWW
Group 179, IL_44465.1  has acceptance rules  -3.9728 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.9728 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    83.00%, min    83.00%,   9 3D sequences,     0 alignment sequences,  8111 random sequences, 1379 random matches,  6 NTs, cWW-L-R-cWW
Group 180, IL_44624.1  has acceptance rules  -8.0579 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.0579 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.60%, min    97.60%,   2 3D sequences,     0 alignment sequences,   583 random sequences,   14 random matches, 14 NTs, cWW-tWH-cWW-L-cWW-tSS-cSS-cWW-L
Group 181, IL_44874.1  has acceptance rules  -6.4783 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.4783 - AlignmentScore) +   3.0000 * CoreEdit <=  18.9524, method  6,TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences,  7265 random sequences,  291 random matches, 11 NTs, cWW-tSH-tHW-L-cWW-L-L
Group 182, IL_45444.1  has acceptance rules  -5.2814 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.2814 - AlignmentScore) +   3.0000 * CoreEdit <=  17.1460, method  6,TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 12281 random sequences,  491 random matches,  9 NTs, cWW-L-R-L-R-L-cWW
Group 183, IL_45896.1  has acceptance rules -18.9206 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-18.9206 - AlignmentScore) +   3.0000 * CoreEdit <=  20.8000, method  1,TP   100.00%, TN    87.50%, min    87.50%,   1 3D sequences,     0 alignment sequences,     8 random sequences,    1 random matches, 11 NTs, cWW-cWW-cWW
Group 184, IL_46086.1  has acceptance rules  -5.7785 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.7785 - AlignmentScore) +   3.0000 * CoreEdit <=  14.1733, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 11839 random sequences,  474 random matches,  8 NTs, cWW-L-cWW-L-L-R
Group 185, IL_46112.1  has acceptance rules  -8.6535 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.6535 - AlignmentScore) +   3.0000 * CoreEdit <=  16.4913, method  6,TP   100.00%, TN    95.89%, min    95.89%,   1 3D sequences,     0 alignment sequences,  4984 random sequences,  205 random matches,  9 NTs, cWW-L-cWW-L-L-R-L
Group 186, IL_46174.3  has acceptance rules  -8.7917 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.7917 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    96.66%, min    96.66%,   5 3D sequences,     0 alignment sequences,  1588 random sequences,   53 random matches, 12 NTs, cWW-cSS-tSS-tSH-L-cWW-tHW-cWW
Group 187, IL_46387.1  has acceptance rules  -6.0473 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.0473 - AlignmentScore) +   3.0000 * CoreEdit <=   9.6667, method  6,TP   100.00%, TN    96.00%, min    96.00%,   3 3D sequences,     0 alignment sequences, 12147 random sequences,  486 random matches,  8 NTs, cWW-cWW-L-cWW-L
Group 188, IL_47074.2  has acceptance rules  -3.3677 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.3677 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    94.75%, min    94.75%,   4 3D sequences,     0 alignment sequences, 10391 random sequences,  546 random matches,  6 NTs, cWW-L-cWW-L
Group 189, IL_47078.3  has acceptance rules  -5.3866 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.3866 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    95.97%, min    95.97%,   4 3D sequences,     0 alignment sequences,  8436 random sequences,  340 random matches,  7 NTs, cWW-cWS-L-cWW-L
Group 190, IL_47087.1  has acceptance rules  -6.0951 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.0951 - AlignmentScore) +   3.0000 * CoreEdit <=  18.7590, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences,  5905 random sequences,  236 random matches, 11 NTs, cWW-L-cWW-L-cWW-tWH-L-L
Group 191, IL_47108.1  has acceptance rules  -6.2610 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.2610 - AlignmentScore) +   3.0000 * CoreEdit <=  16.1809, method  6,TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences, 13189 random sequences,  529 random matches,  9 NTs, cWW-L-R-L-tHH-L-cWW
Group 192, IL_47346.2  has acceptance rules  -6.1326 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.1326 - AlignmentScore) +   3.0000 * CoreEdit <=  18.3337, method  6,TP   100.00%, TN    95.99%, min    95.99%,   7 3D sequences,     0 alignment sequences,  2771 random sequences,  111 random matches, 12 NTs, cWW-tSH-L-R-tHH-tHS-cWW
Group 193, IL_47972.1  has acceptance rules  -5.3631 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.3631 - AlignmentScore) +   3.0000 * CoreEdit <=  11.9911, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 14489 random sequences,  580 random matches,  8 NTs, cWW-L-R-L-cWW-L
Group 194, IL_48076.6  has acceptance rules  -3.3226 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.3226 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    92.71%, min    92.71%,  41 3D sequences,     0 alignment sequences,  6156 random sequences,  449 random matches,  5 NTs, cWW-cSH-cWW
Group 195, IL_48444.6  has acceptance rules  -7.8168 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.8168 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    95.80%, min    95.80%,   4 3D sequences,     0 alignment sequences, 18636 random sequences,  782 random matches,  8 NTs, cWW-L-R-cWW-cWW
Group 196, IL_49061.1  has acceptance rules  -7.2469 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.2469 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    95.69%, min    95.69%,   6 3D sequences,     0 alignment sequences, 18267 random sequences,  788 random matches,  8 NTs, cWW-L-R-L-cWW-L
Group 197, IL_49612.1  has acceptance rules -10.7763 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-10.7763 - AlignmentScore) +   3.0000 * CoreEdit <=  14.5679, method  6,TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 18715 random sequences,  749 random matches, 10 NTs, cWW-L-R-L-R-L-cWW-L
Group 198, IL_49714.1  has acceptance rules  -4.5706 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.5706 - AlignmentScore) +   3.0000 * CoreEdit <=  13.2236, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences,  7568 random sequences,  303 random matches,  7 NTs, cWW-L-cWW-L-L
Group 199, IL_49751.4  has acceptance rules  -7.2614 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.2614 - AlignmentScore) +   3.0000 * CoreEdit <=  11.2956, method  6,TP   100.00%, TN    96.01%, min    96.01%,  16 3D sequences,     0 alignment sequences,  6486 random sequences,  259 random matches, 10 NTs, cWW-cWW-cWW-cWW-cWW
Group 200, IL_49767.8  has acceptance rules  -6.7495 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.7495 - AlignmentScore) +   3.0000 * CoreEdit <=  15.8484, method  6,TP   100.00%, TN    96.00%, min    96.00%,   6 3D sequences,     0 alignment sequences,  5547 random sequences,  222 random matches, 11 NTs, cWW-cWW-tWH-L-tHS-cWW
Group 201, IL_49867.1  has acceptance rules  -7.3205 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.3205 - AlignmentScore) +   3.0000 * CoreEdit <=  23.6130, method  8,TP   100.00%, TN    97.96%, min    97.96%,   1 3D sequences,     0 alignment sequences,   294 random sequences,    6 random matches, 15 NTs, cWW-cWW-L-R-L-R-tHW-R-L-L-cWW
Group 202, IL_49971.1  has acceptance rules  -5.8516 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.8516 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    96.06%, min    96.06%,   1 3D sequences,     0 alignment sequences,  1929 random sequences,   76 random matches, 10 NTs, cWW-cWH-cWW-cWW-L-L-R
Group 203, IL_50694.7  has acceptance rules  -3.4958 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.4958 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    91.66%, min    91.66%,  27 3D sequences,     0 alignment sequences,  5347 random sequences,  446 random matches,  6 NTs, cWW-tSH-cWW-L
Group 204, IL_50715.3  has acceptance rules -14.8806 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-14.8806 - AlignmentScore) +   3.0000 * CoreEdit <=  25.0000, method  1,TP   100.00%, TN   100.00%, min   100.00%,   4 3D sequences,     0 alignment sequences,     1 random sequences,    0 random matches, 21 NTs, cWW-tSH-tHH-L-R-L-R-L-tWW-L-cWW-L-L-L-R-L
Group 205, IL_50730.2  has acceptance rules  -6.3745 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.3745 - AlignmentScore) +   3.0000 * CoreEdit <=  10.5840, method  6,TP   100.00%, TN    96.00%, min    96.00%,  19 3D sequences,     0 alignment sequences,  4898 random sequences,  196 random matches, 10 NTs, cWW-tSH-tHS-tHS-cWW
Group 206, IL_51191.1  has acceptance rules  -6.9316 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.9316 - AlignmentScore) +   3.0000 * CoreEdit <=  17.0962, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 15111 random sequences,  604 random matches,  9 NTs, cWW-L-R-L-cWW-L-L
Group 207, IL_51265.3  has acceptance rules  -4.5912 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.5912 - AlignmentScore) +   3.0000 * CoreEdit <=  15.7706, method  6,TP   100.00%, TN    96.01%, min    96.01%,   6 3D sequences,     0 alignment sequences,  3258 random sequences,  130 random matches, 10 NTs, cWW-tSS-tHS-tSH-cWW-L
Group 208, IL_51387.2  has acceptance rules  -4.9486 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.9486 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    95.14%, min    95.14%,  20 3D sequences,     0 alignment sequences,  9711 random sequences,  472 random matches,  7 NTs, cWW-cSH-cWW-cWW
Group 209, IL_51454.3  has acceptance rules  -2.7382 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -2.7382 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    95.08%, min    95.08%,  45 3D sequences,     0 alignment sequences,  5792 random sequences,  285 random matches,  5 NTs, cWW-cSH-cWW
Group 210, IL_51479.1  has acceptance rules  -6.9950 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.9950 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    93.24%, min    93.24%,  10 3D sequences,     0 alignment sequences, 12127 random sequences,  820 random matches,  7 NTs, cWW-L-R-L-cWW
Group 211, IL_52743.1  has acceptance rules  -3.9423 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.9423 - AlignmentScore) +   3.0000 * CoreEdit <=  17.8493, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences,  3874 random sequences,  155 random matches, 10 NTs, cWW-tSW-L-cSW-L-cWW-L
Group 212, IL_53448.1  has acceptance rules  -4.0244 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.0244 - AlignmentScore) +   3.0000 * CoreEdit <=  16.5517, method  6,TP   100.00%, TN    95.96%, min    95.96%,  11 3D sequences,     0 alignment sequences,  5821 random sequences,  235 random matches,  8 NTs, cWW-tWH-cSH-cWW
Group 213, IL_53581.1  has acceptance rules  -7.6695 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.6695 - AlignmentScore) +   3.0000 * CoreEdit <=  25.0000, method 12,TP   100.00%, TN      NaN%, min   100.00%,   2 3D sequences,     0 alignment sequences,     0 random sequences,    0 random matches, 22 NTs, cWW-tWW-L-tWH-cSS-tSS-tWH-cSS-tWH-R-tSS-R-L-L-cWW-L-cWW
Group 214, IL_53596.1  has acceptance rules  -7.2788 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.2788 - AlignmentScore) +   3.0000 * CoreEdit <=  17.8037, method  6,TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences,  6793 random sequences,  272 random matches,  9 NTs, cWW-L-cWW-L-L-R-L
Group 215, IL_53787.1  has acceptance rules -10.4803 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-10.4803 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.48%, min    97.48%,   1 3D sequences,     0 alignment sequences,   318 random sequences,    8 random matches, 14 NTs, cWW-L-cWW-L-L-R-L-R-L-R-L-R
Group 216, IL_54041.2  has acceptance rules  -6.0504 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.0504 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    96.80%, min    96.80%,   7 3D sequences,     0 alignment sequences,  3438 random sequences,  110 random matches, 11 NTs, cWW-L-R-L-R-tWH-L-cWW
Group 217, IL_54050.1  has acceptance rules -10.4862 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-10.4862 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.90%, min    97.90%,   1 3D sequences,     0 alignment sequences,   381 random sequences,    8 random matches, 11 NTs, cWW-L-R-L-R-L-cWW-L-L
Group 218, IL_54177.4  has acceptance rules  -5.3135 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.3135 - AlignmentScore) +   3.0000 * CoreEdit <=  23.6131, method  8,TP   100.00%, TN    97.78%, min    97.78%,   4 3D sequences,     0 alignment sequences,   225 random sequences,    5 random matches, 13 NTs, cWW-cSW-tWH-L-R-L-R-tHS-cWW
Group 219, IL_54737.1  has acceptance rules -20.9955 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-20.9955 - AlignmentScore) +   3.0000 * CoreEdit <=  25.0000, method 12,TP   100.00%, TN      NaN%, min   100.00%,   1 3D sequences,     0 alignment sequences,     0 random sequences,    0 random matches, 20 NTs, cWW-L-R-L-R-L-R-L-R-L-R-L-R-L-R-L-R-L-R
Group 220, IL_54896.1  has acceptance rules  -9.0456 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.0456 - AlignmentScore) +   3.0000 * CoreEdit <=  19.0497, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences,  4847 random sequences,  194 random matches, 12 NTs, cWW-L-R-L-cWW-L-L-R-L-R
Group 221, IL_55516.2  has acceptance rules  -5.6175 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.6175 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    94.07%, min    94.07%,   7 3D sequences,     0 alignment sequences, 13540 random sequences,  803 random matches,  7 NTs, cWW-cWW-cSH-cWW
Group 222, IL_55917.1  has acceptance rules  -8.2822 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.2822 - AlignmentScore) +   3.0000 * CoreEdit <=  18.1958, method  6,TP   100.00%, TN    96.01%, min    96.01%,   1 3D sequences,     0 alignment sequences,  6310 random sequences,  252 random matches,  8 NTs, cWW-L-cWW-L-L-R
Group 223, IL_55953.3  has acceptance rules  -4.4409 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.4409 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    96.32%, min    96.32%,   4 3D sequences,     0 alignment sequences,  2091 random sequences,   77 random matches, 12 NTs, cWW-tSH-tHS-R-L-L-R-cWW
Group 224, IL_56317.1  has acceptance rules  -6.1986 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.1986 - AlignmentScore) +   3.0000 * CoreEdit <=  18.4796, method  6,TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences,  9572 random sequences,  383 random matches,  9 NTs, cWW-L-R-L-R-L-cWW
Group 225, IL_56455.6  has acceptance rules  -9.6474 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.6474 - AlignmentScore) +   3.0000 * CoreEdit <=  23.4229, method  8,TP   100.00%, TN    98.65%, min    98.65%,   7 3D sequences,     0 alignment sequences,    74 random sequences,    1 random matches, 18 NTs, cWW-tSH-tHW-L-R-L-R-L-R-tWH-tHS-cWW
Group 226, IL_56987.1  has acceptance rules  -4.1600 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.1600 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    87.11%, min    87.11%,   3 3D sequences,     0 alignment sequences,  8720 random sequences, 1124 random matches,  5 NTs, cWW-L-cWW
Group 227, IL_57188.5  has acceptance rules  -6.6464 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.6464 - AlignmentScore) +   3.0000 * CoreEdit <=  19.0266, method  6,TP   100.00%, TN    95.99%, min    95.99%,   5 3D sequences,     0 alignment sequences,  2716 random sequences,  109 random matches, 11 NTs, cWW-tWW-L-tWW-cWW-cSH
Group 228, IL_57741.1  has acceptance rules -10.7017 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-10.7017 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    96.36%, min    96.36%,   1 3D sequences,     0 alignment sequences,    55 random sequences,    2 random matches, 16 NTs, cWW-L-R-L-R-L-R-L-R-L-cWW-L-cWW
Group 229, IL_57744.1  has acceptance rules  -4.9111 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.9111 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    83.92%, min    83.92%,  22 3D sequences,     0 alignment sequences,  7287 random sequences, 1172 random matches,  6 NTs, cWW-cWW-cWW
Group 230, IL_57881.1  has acceptance rules  -6.5784 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.5784 - AlignmentScore) +   3.0000 * CoreEdit <=  10.3175, method  6,TP   100.00%, TN    95.98%, min    95.98%,   1 3D sequences,     0 alignment sequences, 16730 random sequences,  672 random matches,  5 NTs, cWW-L-cWW
Group 231, IL_58103.11 has acceptance rules  -2.7703 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -2.7703 - AlignmentScore) +   3.0000 * CoreEdit <=  16.1921, method  6,TP   100.00%, TN    95.97%, min    95.97%,   9 3D sequences,     0 alignment sequences,  1215 random sequences,   49 random matches, 10 NTs, cWW-cSH-cWS-L-tSW-R-R-cWW
Group 232, IL_58112.2  has acceptance rules  -7.0700 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.0700 - AlignmentScore) +   3.0000 * CoreEdit <=   9.7359, method  6,TP   100.00%, TN    95.99%, min    95.99%,   4 3D sequences,     0 alignment sequences, 11526 random sequences,  462 random matches,  8 NTs, cWW-cWW-L-R-cWW
Group 233, IL_58126.1  has acceptance rules -11.4192 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-11.4192 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.47%, min    97.47%,   2 3D sequences,     0 alignment sequences,  1662 random sequences,   42 random matches, 15 NTs, cWW-L-R-L-R-L-R-L-R-L-R-L-cWW
Group 234, IL_58350.1  has acceptance rules  -8.2231 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.2231 - AlignmentScore) +   3.0000 * CoreEdit <=  21.1471, method  8,TP   100.00%, TN    98.00%, min    98.00%,   1 3D sequences,     0 alignment sequences,  1298 random sequences,   26 random matches, 14 NTs, cWW-L-R-tWH-tWH-L-R-L-cWW-L
Group 235, IL_58960.1  has acceptance rules  -6.1288 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.1288 - AlignmentScore) +   3.0000 * CoreEdit <=  17.4128, method  6,TP   100.00%, TN    95.99%, min    95.99%,   3 3D sequences,     0 alignment sequences,  4867 random sequences,  195 random matches, 11 NTs, cWW-L-cWW-L-tWW-L-R-L
Group 236, IL_59049.1  has acceptance rules  -8.8977 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.8977 - AlignmentScore) +   3.0000 * CoreEdit <=  21.8028, method  8,TP   100.00%, TN    98.10%, min    98.10%,   2 3D sequences,     0 alignment sequences,   315 random sequences,    6 random matches, 16 NTs, cWW-cWW-L-R-L-R-L-R-L-R-L-cWW-L
Group 237, IL_59258.1  has acceptance rules  -7.5992 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.5992 - AlignmentScore) +   3.0000 * CoreEdit <=  19.2673, method  6,TP   100.00%, TN    95.98%, min    95.98%,   1 3D sequences,     0 alignment sequences,  7089 random sequences,  285 random matches, 12 NTs, cWW-L-R-L-R-L-cWW-L-cWW
Group 238, IL_59302.1  has acceptance rules  -6.4258 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.4258 - AlignmentScore) +   3.0000 * CoreEdit <=  13.3175, method  6,TP   100.00%, TN    95.98%, min    95.98%,   2 3D sequences,     0 alignment sequences, 16609 random sequences,  668 random matches,  9 NTs, cWW-L-R-L-cWW-L
Group 239, IL_59724.1  has acceptance rules  -6.2989 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.2989 - AlignmentScore) +   3.0000 * CoreEdit <=  20.6757, method  8,TP   100.00%, TN    98.11%, min    98.11%,   1 3D sequences,     0 alignment sequences,   106 random sequences,    2 random matches, 15 NTs, cWW-L-R-L-R-cSH-tWH-tHS-R-L-cWW
Group 240, IL_59877.1  has acceptance rules  -2.8610 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -2.8610 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    93.21%, min    93.21%,   2 3D sequences,     0 alignment sequences,  8745 random sequences,  594 random matches,  5 NTs, cWW-L-cWW
Group 241, IL_60448.1  has acceptance rules -10.0383 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-10.0383 - AlignmentScore) +   3.0000 * CoreEdit <=  25.0000, method  1,TP   100.00%, TN    50.00%, min    50.00%,   1 3D sequences,     0 alignment sequences,     2 random sequences,    1 random matches, 20 NTs, cWW-L-cWW-L-R-L-tWH-L-tHS-L-R-L-cWW-L-R
Group 242, IL_60657.1  has acceptance rules -10.5146 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-10.5146 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    96.12%, min    96.12%,   1 3D sequences,     0 alignment sequences,   309 random sequences,   12 random matches, 16 NTs, cWW-cWW-L-R-L-cWW-L-L-R-L-R-L-R
Group 243, IL_60797.1  has acceptance rules  -9.5598 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.5598 - AlignmentScore) +   3.0000 * CoreEdit <=  25.0000, method  1,TP   100.00%, TN   100.00%, min   100.00%,   4 3D sequences,     0 alignment sequences,    15 random sequences,    0 random matches, 17 NTs, cWW-cWW-tSH-tHW-tHW-L-R-L-cWW-cWW
Group 244, IL_61242.1  has acceptance rules  -5.2390 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.2390 - AlignmentScore) +   3.0000 * CoreEdit <=  18.2592, method  6,TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences,  5339 random sequences,  214 random matches, 10 NTs, cWW-cWW-L-R-L-R-cWW
Group 245, IL_61249.1  has acceptance rules -10.8617 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-10.8617 - AlignmentScore) +   3.0000 * CoreEdit <=  25.0000, method  1,TP   100.00%, TN   100.00%, min   100.00%,   1 3D sequences,     0 alignment sequences,     4 random sequences,    0 random matches, 20 NTs, cWW-L-R-L-R-tHS-cWW-cWW-tSH-tHS-cWW-cWW
Group 246, IL_61258.15 has acceptance rules  -2.5432 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -2.5432 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    85.87%, min    85.87%,  41 3D sequences,     0 alignment sequences,  4559 random sequences,  644 random matches,  5 NTs, cWW-L-cWW
Group 247, IL_61286.1  has acceptance rules  -7.6353 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.6353 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.98%, min    97.98%,   1 3D sequences,     0 alignment sequences,  2677 random sequences,   54 random matches, 14 NTs, cWW-L-R-L-R-L-tWH-L-tHS-cWW
Group 248, IL_61299.4  has acceptance rules  -5.9841 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.9841 - AlignmentScore) +   3.0000 * CoreEdit <=  12.6547, method  6,TP   100.00%, TN    95.98%, min    95.98%,   3 3D sequences,     0 alignment sequences,  8384 random sequences,  337 random matches,  9 NTs, cWW-L-R-L-cWW-L-L
Group 249, IL_61341.1  has acceptance rules  -6.9381 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.9381 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    90.37%, min    90.37%,   2 3D sequences,     0 alignment sequences, 13847 random sequences, 1334 random matches,  6 NTs, cWW-L-R-L-cWW
Group 250, IL_61438.4  has acceptance rules  -2.7299 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -2.7299 - AlignmentScore) +   3.0000 * CoreEdit <=  10.7838, method  6,TP   100.00%, TN    96.00%, min    96.00%,   4 3D sequences,     0 alignment sequences,  8997 random sequences,  360 random matches,  5 NTs, cWW-L-cWW
Group 251, IL_61440.1  has acceptance rules  -6.9696 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.9696 - AlignmentScore) +   3.0000 * CoreEdit <=  13.0366, method  6,TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences,  5214 random sequences,  209 random matches, 10 NTs, cWW-tSH-tHS-tWS-cWW
Group 252, IL_61476.2  has acceptance rules  -5.0301 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.0301 - AlignmentScore) +   3.0000 * CoreEdit <=  10.8912, method  6,TP   100.00%, TN    95.99%, min    95.99%,   7 3D sequences,     0 alignment sequences, 10987 random sequences,  441 random matches,  8 NTs, cWW-tSH-L-cWW-L
Group 253, IL_62012.1  has acceptance rules  -6.3787 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.3787 - AlignmentScore) +   3.0000 * CoreEdit <=  13.4561, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 12641 random sequences,  506 random matches,  9 NTs, cWW-cWW-L-R-L-cWW
Group 254, IL_62654.1  has acceptance rules  -8.3930 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.3930 - AlignmentScore) +   3.0000 * CoreEdit <=  14.9328, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences,  7733 random sequences,  309 random matches, 10 NTs, cWW-tSH-tHH-tHS-cWW
Group 255, IL_63519.1  has acceptance rules  -6.3177 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.3177 - AlignmentScore) +   3.0000 * CoreEdit <=  15.5541, method  6,TP   100.00%, TN    95.99%, min    95.99%,   2 3D sequences,     0 alignment sequences,  7013 random sequences,  281 random matches,  9 NTs, cWW-cWW-L-R-cSH-cWW
Group 256, IL_63596.11 has acceptance rules  -3.3559 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.3559 - AlignmentScore) +   3.0000 * CoreEdit <=  12.2486, method  6,TP   100.00%, TN    95.98%, min    95.98%,  19 3D sequences,     0 alignment sequences,  4898 random sequences,  197 random matches,  7 NTs, cWW-cWS-cSH-tWH-cWW-L
Group 257, IL_63775.1  has acceptance rules  -3.1649 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.1649 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    82.29%, min    82.29%,   1 3D sequences,     0 alignment sequences,  5376 random sequences,  952 random matches,  5 NTs, cWW-L-cWW
Group 258, IL_64048.1  has acceptance rules  -6.0564 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.0564 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.40%, min    97.40%,   2 3D sequences,     0 alignment sequences,  3417 random sequences,   89 random matches, 11 NTs, cWW-L-cWW-L-L-tWH-R-L-R
Group 259, IL_64231.5  has acceptance rules  -6.6789 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.6789 - AlignmentScore) +   3.0000 * CoreEdit <=   9.8183, method  6,TP   100.00%, TN    96.00%, min    96.00%,  11 3D sequences,     0 alignment sequences, 11689 random sequences,  468 random matches,  9 NTs, cWW-cWW-L-R-L-cWW
Group 260, IL_64403.1  has acceptance rules -10.3733 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-10.3733 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    98.04%, min    98.04%,   1 3D sequences,     0 alignment sequences,   510 random sequences,   10 random matches, 14 NTs, cWW-L-R-L-R-L-R-L-cWW-L-L-R
Group 261, IL_64842.1  has acceptance rules  -6.4917 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.4917 - AlignmentScore) +   3.0000 * CoreEdit <=  18.9722, method  6,TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences,  8375 random sequences,  336 random matches, 10 NTs, cWW-L-tWH-L-cWW-L-cSH
Group 262, IL_64858.3  has acceptance rules  -9.1793 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.1793 - AlignmentScore) +   3.0000 * CoreEdit <=  25.0000, method 12,TP   100.00%, TN      NaN%, min   100.00%,   6 3D sequences,     0 alignment sequences,     0 random sequences,    0 random matches, 22 NTs, cWW-cHW-cWH-R-L-cWH-cHW-cHW-cWH-cWH-cHW-L-cWW-L-R-cWW-L-cWW
Group 263, IL_64900.1  has acceptance rules  -7.4899 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.4899 - AlignmentScore) +   3.0000 * CoreEdit <=  20.4463, method  8,TP   100.00%, TN    97.98%, min    97.98%,   3 3D sequences,     0 alignment sequences,   645 random sequences,   13 random matches, 14 NTs, cWW-cWW-tSS-tSH-L-tHS-R-cWW-L
Group 264, IL_65594.1  has acceptance rules  -8.2587 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.2587 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.83%, min    97.83%,   2 3D sequences,     0 alignment sequences,   461 random sequences,   10 random matches, 15 NTs, cWW-L-R-tSW-tHH-cSH-tWH-tHS-cWW
Group 265, IL_65653.1  has acceptance rules  -7.6613 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.6613 - AlignmentScore) +   3.0000 * CoreEdit <=  20.4315, method  8,TP   100.00%, TN    97.06%, min    97.06%,   4 3D sequences,     0 alignment sequences,    34 random sequences,    1 random matches, 16 NTs, cWW-tSW-tHW-tWW-tWH-cSH-L-L-tHS-L-cWW-L
Group 266, IL_65718.4  has acceptance rules  -5.7065 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.7065 - AlignmentScore) +   3.0000 * CoreEdit <=  15.3419, method  6,TP   100.00%, TN    96.01%, min    96.01%,   4 3D sequences,     0 alignment sequences,  7010 random sequences,  280 random matches,  9 NTs, cWW-cSH-cWS-cWW-cWW
Group 267, IL_65851.3  has acceptance rules  -5.7492 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.7492 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.36%, min    97.36%,   2 3D sequences,     0 alignment sequences,   227 random sequences,    6 random matches, 14 NTs, cWW-cWW-cWW-cWW-R-tHW-tSH-tHS-L
Group 268, IL_66635.5  has acceptance rules  -4.7234 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.7234 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    85.39%, min    85.39%,  27 3D sequences,     0 alignment sequences,  8900 random sequences, 1300 random matches,  5 NTs, cWW-L-cWW
Group 269, IL_66663.1  has acceptance rules -10.0172 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-10.0172 - AlignmentScore) +   3.0000 * CoreEdit <=  22.1003, method  8,TP   100.00%, TN    97.14%, min    97.14%,   1 3D sequences,     0 alignment sequences,    35 random sequences,    1 random matches, 15 NTs, cWW-L-tHS-tSW-tWH-cWH-cWW-L-cWW
Group 270, IL_66798.2  has acceptance rules  -4.8384 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.8384 - AlignmentScore) +   3.0000 * CoreEdit <=  14.3647, method  6,TP   100.00%, TN    96.00%, min    96.00%,   6 3D sequences,     0 alignment sequences,  6775 random sequences,  271 random matches, 10 NTs, cWW-L-R-L-R-tHS-cWW
Group 271, IL_66997.2  has acceptance rules  -5.8873 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.8873 - AlignmentScore) +   3.0000 * CoreEdit <=  11.1976, method  6,TP   100.00%, TN    95.98%, min    95.98%,   2 3D sequences,     0 alignment sequences, 12977 random sequences,  522 random matches,  8 NTs, cWW-L-R-L-cWW-L
Group 272, IL_67095.2  has acceptance rules  -4.1754 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.1754 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    85.72%, min    85.72%,   8 3D sequences,     0 alignment sequences,  7005 random sequences, 1000 random matches,  6 NTs, cWW-tWW-cWW
Group 273, IL_67623.1  has acceptance rules  -6.1591 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.1591 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    96.24%, min    96.24%,   1 3D sequences,     0 alignment sequences,   186 random sequences,    7 random matches, 14 NTs, cWW-tSW-cSW-L-cSW-L-R-L-cWW-cWW
Group 274, IL_67767.4  has acceptance rules  -4.1338 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.1338 - AlignmentScore) +   3.0000 * CoreEdit <=  16.5713, method  6,TP   100.00%, TN    96.01%, min    96.01%,   7 3D sequences,     0 alignment sequences,  3784 random sequences,  151 random matches,  9 NTs, cWW-tWH-cWW-cSH-cWW
Group 275, IL_67780.1  has acceptance rules  -6.8769 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.8769 - AlignmentScore) +   3.0000 * CoreEdit <=  14.6676, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences,  8644 random sequences,  346 random matches, 10 NTs, cWW-cSH-L-R-L-L-R-L
Group 276, IL_68140.4  has acceptance rules  -3.2629 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.2629 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    93.11%, min    93.11%,  18 3D sequences,     0 alignment sequences,  6259 random sequences,  431 random matches,  6 NTs, cWW-cSH-cWW
Group 277, IL_68243.1  has acceptance rules  -6.1763 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.1763 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.66%, min    97.66%,   1 3D sequences,     0 alignment sequences,   984 random sequences,   23 random matches, 13 NTs, cWW-L-cWW-cWW-R-L-tHS-cWW
Group 278, IL_68405.1  has acceptance rules  -7.7027 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.7027 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    96.60%, min    96.60%,   1 3D sequences,     0 alignment sequences,  3531 random sequences,  120 random matches, 11 NTs, cWW-cSS-L-tWH-tHW-cWW-cWW
Group 279, IL_68574.4  has acceptance rules  -5.7960 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.7960 - AlignmentScore) +   3.0000 * CoreEdit <=  12.5097, method  6,TP   100.00%, TN    96.00%, min    96.00%,   3 3D sequences,     0 alignment sequences,  8498 random sequences,  340 random matches,  8 NTs, cWW-tHH-tHS-cWW
Group 280, IL_68909.1  has acceptance rules  -8.7029 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.7029 - AlignmentScore) +   3.0000 * CoreEdit <=  10.3075, method  6,TP   100.00%, TN    96.00%, min    96.00%,   6 3D sequences,     0 alignment sequences, 15283 random sequences,  611 random matches,  9 NTs, cWW-L-R-L-R-L-cWW
Group 281, IL_69000.1  has acceptance rules  -5.3967 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.3967 - AlignmentScore) +   3.0000 * CoreEdit <=  15.7392, method  6,TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 12661 random sequences,  507 random matches,  9 NTs, cWW-L-cWW-L-cWW-L
Group 282, IL_69145.3  has acceptance rules  -4.2307 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.2307 - AlignmentScore) +   3.0000 * CoreEdit <=  18.0319, method  6,TP   100.00%, TN    96.00%, min    96.00%,   4 3D sequences,     0 alignment sequences, 10330 random sequences,  413 random matches, 10 NTs, cWW-L-cWW-L-R-L-R-R
Group 283, IL_69229.3  has acceptance rules  -7.8603 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.8603 - AlignmentScore) +   3.0000 * CoreEdit <=  19.8075, method  6,TP   100.00%, TN    96.00%, min    96.00%,   8 3D sequences,     0 alignment sequences,  4247 random sequences,  170 random matches, 12 NTs, cWW-L-tSH-L-tHS-cWW-cWW
Group 284, IL_69271.3  has acceptance rules  -7.9158 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.9158 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.64%, min    97.64%,   2 3D sequences,     0 alignment sequences,  2369 random sequences,   56 random matches, 12 NTs, cWW-cWW-L-R-L-cWW-L-L-R
Group 285, IL_69440.3  has acceptance rules  -4.9277 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.9277 - AlignmentScore) +   3.0000 * CoreEdit <=  11.2708, method  6,TP   100.00%, TN    95.94%, min    95.94%,   3 3D sequences,     0 alignment sequences, 12042 random sequences,  489 random matches,  8 NTs, cWW-L-R-cSH-cWW
Group 286, IL_69543.3  has acceptance rules  -8.3002 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.3002 - AlignmentScore) +   3.0000 * CoreEdit <=  19.4172, method  6,TP   100.00%, TN    96.00%, min    96.00%,   3 3D sequences,     0 alignment sequences,  2624 random sequences,  105 random matches, 12 NTs, cWW-tSH-L-R-tSS-tHS-L-R-cWW
Group 287, IL_69986.1  has acceptance rules  -6.6940 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.6940 - AlignmentScore) +   3.0000 * CoreEdit <=  19.6433, method  6,TP   100.00%, TN    95.98%, min    95.98%,   1 3D sequences,     0 alignment sequences,  2090 random sequences,   84 random matches, 12 NTs, cWW-cHW-L-R-L-R-cWH-cWW
Group 288, IL_70096.1  has acceptance rules  -6.8273 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.8273 - AlignmentScore) +   3.0000 * CoreEdit <=  17.3802, method  6,TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences,  9519 random sequences,  382 random matches,  7 NTs, cWW-L-cWW-cWW
Group 289, IL_70335.1  has acceptance rules  -5.4816 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.4816 - AlignmentScore) +   3.0000 * CoreEdit <=  14.8485, method  6,TP   100.00%, TN    95.99%, min    95.99%,   2 3D sequences,     0 alignment sequences, 14671 random sequences,  588 random matches,  7 NTs, cWW-L-R-L-cWW
Group 290, IL_70376.1  has acceptance rules  -5.1466 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.1466 - AlignmentScore) +   3.0000 * CoreEdit <=  12.6066, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 13505 random sequences,  540 random matches,  6 NTs, cWW-L-cWW-L
Group 291, IL_70411.2  has acceptance rules  -5.4889 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.4889 - AlignmentScore) +   3.0000 * CoreEdit <=  16.8439, method  6,TP   100.00%, TN    96.00%, min    96.00%,   7 3D sequences,     0 alignment sequences,  5145 random sequences,  206 random matches, 10 NTs, cWW-tSH-L-tHH-L-cWW
Group 292, IL_70627.3  has acceptance rules  -6.7308 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.7308 - AlignmentScore) +   3.0000 * CoreEdit <=  16.3388, method  6,TP   100.00%, TN    96.00%, min    96.00%,   3 3D sequences,     0 alignment sequences, 13306 random sequences,  532 random matches, 10 NTs, cWW-L-R-tHW-cWW
Group 293, IL_70670.1  has acceptance rules -12.3312 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-12.3312 - AlignmentScore) +   3.0000 * CoreEdit <=  22.1071, method  8,TP   100.00%, TN    97.84%, min    97.84%,   1 3D sequences,     0 alignment sequences,   185 random sequences,    4 random matches, 18 NTs, cWW-R-L-R-L-R-L-R-L-R-L-R-tWH-L-R-L
Group 294, IL_70801.1  has acceptance rules  -6.8858 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.8858 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.48%, min    97.48%,   1 3D sequences,     0 alignment sequences,  2301 random sequences,   58 random matches, 13 NTs, cWW-cWW-L-R-tWW-L-R-L-cWW
Group 295, IL_70923.9  has acceptance rules  -5.4957 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.4957 - AlignmentScore) +   3.0000 * CoreEdit <=  18.2161, method  6,TP   100.00%, TN    96.00%, min    96.00%,  27 3D sequences,     0 alignment sequences,  2249 random sequences,   90 random matches, 12 NTs, cWW-tSS-tSH-L-tHS-tHS-cWW
Group 296, IL_71294.3  has acceptance rules  -7.9291 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.9291 - AlignmentScore) +   3.0000 * CoreEdit <=  17.9316, method  6,TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences,  6203 random sequences,  248 random matches, 12 NTs, cWW-L-R-L-R-L-R-L-R-cWW
Group 297, IL_71598.1  has acceptance rules  -6.2181 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.2181 - AlignmentScore) +   3.0000 * CoreEdit <=  11.9830, method  6,TP   100.00%, TN    95.98%, min    95.98%,   1 3D sequences,     0 alignment sequences, 13603 random sequences,  547 random matches,  8 NTs, cWW-tSH-L-cWW-L
Group 298, IL_73002.1  has acceptance rules -12.2297 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-12.2297 - AlignmentScore) +   3.0000 * CoreEdit <=  25.0000, method  1,TP   100.00%, TN    85.00%, min    85.00%,   1 3D sequences,     0 alignment sequences,    20 random sequences,    3 random matches, 16 NTs, cWW-L-R-L-R-L-R-L-R-L-cWW-L-L-R
Group 299, IL_73355.1  has acceptance rules  -3.9345 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.9345 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    85.96%, min    85.96%,   2 3D sequences,     0 alignment sequences,  8867 random sequences, 1245 random matches,  6 NTs, cWW-L-cWW-L
Group 300, IL_73452.2  has acceptance rules  -5.5729 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.5729 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    82.61%, min    82.61%,   3 3D sequences,     0 alignment sequences, 11695 random sequences, 2034 random matches,  5 NTs, cWW-L-cWW
Group 301, IL_73700.1  has acceptance rules  -9.0598 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.0598 - AlignmentScore) +   3.0000 * CoreEdit <=  20.9601, method  8,TP   100.00%, TN    97.37%, min    97.37%,   1 3D sequences,     0 alignment sequences,    76 random sequences,    2 random matches, 13 NTs, cWW-L-R-L-cWW-L-cWW-tHS-cWW
Group 302, IL_73759.1  has acceptance rules  -4.8710 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.8710 - AlignmentScore) +   3.0000 * CoreEdit <=  19.5125, method  6,TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences,  4790 random sequences,  192 random matches,  9 NTs, cWW-cSH-tHS-cWH-cHW-cWW
Group 303, IL_73789.1  has acceptance rules  -4.3606 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.3606 - AlignmentScore) +   3.0000 * CoreEdit <=  15.8228, method  6,TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 11911 random sequences,  477 random matches,  8 NTs, cWW-L-R-L-cWW-L
Group 304, IL_74051.1  has acceptance rules  -4.7926 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.7926 - AlignmentScore) +   3.0000 * CoreEdit <=  19.6349, method  6,TP   100.00%, TN    96.00%, min    96.00%,   3 3D sequences,     0 alignment sequences,  3022 random sequences,  121 random matches, 11 NTs, cWW-tSS-tSH-L-tHS-cWW-L
Group 305, IL_74184.1  has acceptance rules  -8.2609 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.2609 - AlignmentScore) +   3.0000 * CoreEdit <=  18.4377, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences,  5852 random sequences,  234 random matches, 11 NTs, cWW-L-tHS-L-cWW-L-L-L
Group 306, IL_74367.1  has acceptance rules  -5.2470 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.2470 - AlignmentScore) +   3.0000 * CoreEdit <=  16.1047, method  6,TP   100.00%, TN    95.97%, min    95.97%,   2 3D sequences,     0 alignment sequences,  8372 random sequences,  337 random matches, 10 NTs, cWW-L-R-L-R-L-R-cWW
Group 307, IL_74746.1  has acceptance rules -14.5056 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-14.5056 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    96.01%, min    96.01%,   2 3D sequences,     0 alignment sequences,   551 random sequences,   22 random matches, 16 NTs, cWW-L-R-L-R-L-R-L-R-L-R-L-R-cWW
Group 308, IL_74957.1  has acceptance rules  -7.6461 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.6461 - AlignmentScore) +   3.0000 * CoreEdit <=  16.7854, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 10705 random sequences,  428 random matches,  9 NTs, cWW-L-cHW-L-cWW-L
Group 309, IL_75283.2  has acceptance rules  -6.7178 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.7178 - AlignmentScore) +   3.0000 * CoreEdit <=  25.0000, method  1,TP   100.00%, TN    83.33%, min    83.33%,   3 3D sequences,     0 alignment sequences,    18 random sequences,    3 random matches, 18 NTs, cWW-tSS-L-R-L-tHS-L-cWW-L-tWH-tWH-L-L-R
Group 310, IL_75294.1  has acceptance rules  -7.9162 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.9162 - AlignmentScore) +   3.0000 * CoreEdit <=  12.6912, method  6,TP   100.00%, TN    95.99%, min    95.99%,   2 3D sequences,     0 alignment sequences, 16500 random sequences,  661 random matches,  9 NTs, cWW-L-R-L-R-L-cWW
Group 311, IL_76308.6  has acceptance rules  -7.4493 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.4493 - AlignmentScore) +   3.0000 * CoreEdit <=  17.8171, method  6,TP   100.00%, TN    96.01%, min    96.01%,   5 3D sequences,     0 alignment sequences,  3079 random sequences,  123 random matches, 12 NTs, cWW-tSH-tHW-tHS-cWW-cWW
Group 312, IL_76319.5  has acceptance rules  -4.7963 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.7963 - AlignmentScore) +   3.0000 * CoreEdit <=  13.1145, method  6,TP   100.00%, TN    96.00%, min    96.00%,   3 3D sequences,     0 alignment sequences, 11383 random sequences,  455 random matches,  7 NTs, cWW-L-R-L-cWW
Group 313, IL_76460.1  has acceptance rules -12.3350 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-12.3350 - AlignmentScore) +   3.0000 * CoreEdit <=  25.0000, method 12,TP   100.00%, TN      NaN%, min   100.00%,   1 3D sequences,     0 alignment sequences,     0 random sequences,    0 random matches, 22 NTs, cWW-cWW-L-tHS-L-R-L-cWW-L-L-R-L-L-R-L-R-L-R
Group 314, IL_76709.2  has acceptance rules  -4.4358 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.4358 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    85.61%, min    85.61%,   4 3D sequences,     0 alignment sequences,  7816 random sequences, 1125 random matches,  6 NTs, cWW-L-cWW-L
Group 315, IL_76758.2  has acceptance rules  -4.6646 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.6646 - AlignmentScore) +   3.0000 * CoreEdit <=  17.6245, method  6,TP   100.00%, TN    96.00%, min    96.00%,   7 3D sequences,     0 alignment sequences,  8523 random sequences,  341 random matches,  9 NTs, cWW-L-R-L-cWW-L-L
Group 316, IL_77045.1  has acceptance rules  -7.9163 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.9163 - AlignmentScore) +   3.0000 * CoreEdit <=  19.6166, method  6,TP   100.00%, TN    95.97%, min    95.97%,   1 3D sequences,     0 alignment sequences,  3970 random sequences,  160 random matches, 11 NTs, cWW-L-tSW-L-tHW-cWW-L
Group 317, IL_77278.1  has acceptance rules  -7.5339 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.5339 - AlignmentScore) +   3.0000 * CoreEdit <=  21.5435, method  8,TP   100.00%, TN    98.00%, min    98.00%,   2 3D sequences,     0 alignment sequences,  1850 random sequences,   37 random matches, 10 NTs, cWW-tWW-L-tWW-cWW-L
Group 318, IL_77658.1  has acceptance rules  -4.3416 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.3416 - AlignmentScore) +   3.0000 * CoreEdit <=   9.9086, method  6,TP   100.00%, TN    96.00%, min    96.00%,  34 3D sequences,     0 alignment sequences,  5420 random sequences,  217 random matches,  8 NTs, cWW-cWW-cWW-cWW
Group 319, IL_77691.5  has acceptance rules  -6.7254 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.7254 - AlignmentScore) +   3.0000 * CoreEdit <=   9.7721, method  6,TP   100.00%, TN    96.00%, min    96.00%,   7 3D sequences,     0 alignment sequences,  8504 random sequences,  340 random matches,  9 NTs, cWW-tSH-L-R-L-cWW
Group 320, IL_77870.1  has acceptance rules  -8.2020 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.2020 - AlignmentScore) +   3.0000 * CoreEdit <=  20.3811, method  8,TP   100.00%, TN    98.00%, min    98.00%,   2 3D sequences,     0 alignment sequences,  3452 random sequences,   69 random matches, 13 NTs, cWW-L-R-L-tHS-L-cWW-L-cWW
Group 321, IL_78349.3  has acceptance rules -10.1204 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-10.1204 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    96.12%, min    96.12%,   2 3D sequences,     0 alignment sequences,  5776 random sequences,  224 random matches, 13 NTs, cWW-L-R-L-R-L-R-L-cWW-L-L
Group 322, IL_78472.1  has acceptance rules  -9.0330 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.0330 - AlignmentScore) +   3.0000 * CoreEdit <=  19.9662, method  6,TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences,  3244 random sequences,  130 random matches, 13 NTs, cWW-L-R-L-R-L-R-L-cWW-L-L
Group 323, IL_78800.1  has acceptance rules  -4.8895 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.8895 - AlignmentScore) +   3.0000 * CoreEdit <=  12.0696, method  6,TP   100.00%, TN    95.99%, min    95.99%,   2 3D sequences,     0 alignment sequences,  7339 random sequences,  294 random matches,  6 NTs, cWW-cSH-L-cWW
Group 324, IL_79846.1  has acceptance rules -11.4084 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-11.4084 - AlignmentScore) +   3.0000 * CoreEdit <=  25.0000, method  1,TP   100.00%, TN   100.00%, min   100.00%,   1 3D sequences,     0 alignment sequences,     1 random sequences,    0 random matches, 19 NTs, cWW-R-L-L-tWH-cWW-L-L-L-R-L-R-cSH-L-L
Group 325, IL_79895.1  has acceptance rules  -5.0280 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.0280 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    83.78%, min    83.78%,   2 3D sequences,     0 alignment sequences,  9669 random sequences, 1568 random matches,  6 NTs, cWW-L-cWW-L
Group 326, IL_80209.1  has acceptance rules  -9.0533 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.0533 - AlignmentScore) +   3.0000 * CoreEdit <=  19.9884, method  6,TP   100.00%, TN    96.01%, min    96.01%,   1 3D sequences,     0 alignment sequences,  2757 random sequences,  110 random matches, 13 NTs, cWW-cHW-L-cWW-L-L-R-L-R-L
Group 327, IL_80231.1  has acceptance rules  -9.1226 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.1226 - AlignmentScore) +   3.0000 * CoreEdit <=  16.3862, method  6,TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences,  8622 random sequences,  345 random matches, 11 NTs, cWW-L-R-L-R-L-R-tHS-cWW
Group 328, IL_80298.1  has acceptance rules -17.8619 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-17.8619 - AlignmentScore) +   3.0000 * CoreEdit <=  25.0000, method 12,TP   100.00%, TN      NaN%, min   100.00%,   1 3D sequences,     0 alignment sequences,     0 random sequences,    0 random matches, 24 NTs, cWW-L-cWW-L-L-R-L-R-L-R-L-R-L-R-L-R-L-R-L-R-L-R
Group 329, IL_80398.1  has acceptance rules  -5.2704 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.2704 - AlignmentScore) +   3.0000 * CoreEdit <=  10.5220, method  6,TP   100.00%, TN    95.92%, min    95.92%,   1 3D sequences,     0 alignment sequences, 10513 random sequences,  429 random matches,  8 NTs, cWW-L-cSW-L-R-cWW
Group 330, IL_80412.1  has acceptance rules  -8.1335 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.1335 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    96.32%, min    96.32%,   1 3D sequences,     0 alignment sequences,  3373 random sequences,  124 random matches, 11 NTs, cWW-tSW-L-cWW-L-L-R-L
Group 331, IL_80604.6  has acceptance rules  -7.1671 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.1671 - AlignmentScore) +   3.0000 * CoreEdit <=  21.9651, method  8,TP   100.00%, TN    98.01%, min    98.01%,   3 3D sequences,     0 alignment sequences,   804 random sequences,   16 random matches, 14 NTs, cWW-cWW-tWH-tWH-tHW-tHW-cWW
Group 332, IL_80926.1  has acceptance rules  -6.3453 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.3453 - AlignmentScore) +   3.0000 * CoreEdit <=  19.2493, method  6,TP   100.00%, TN    96.01%, min    96.01%,   7 3D sequences,     0 alignment sequences,  4212 random sequences,  168 random matches, 11 NTs, cWW-cWW-tSH-tHS-L-cWW
Group 333, IL_81392.1  has acceptance rules -16.2142 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-16.2142 - AlignmentScore) +   3.0000 * CoreEdit <=  25.0000, method 12,TP   100.00%, TN      NaN%, min   100.00%,   1 3D sequences,     0 alignment sequences,     0 random sequences,    0 random matches, 13 NTs, cWW-L-R-L-R-L-cWW-L-L-R-L
Group 334, IL_81516.2  has acceptance rules  -6.0432 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.0432 - AlignmentScore) +   3.0000 * CoreEdit <=  22.7971, method  8,TP   100.00%, TN    98.31%, min    98.31%,   6 3D sequences,     0 alignment sequences,    59 random sequences,    1 random matches, 16 NTs, cWW-cWS-tSH-L-tWH-cWW-tSS-tSH-L-R-L
Group 335, IL_81522.2  has acceptance rules  -6.3660 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.3660 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    95.28%, min    95.28%,   3 3D sequences,     0 alignment sequences, 17660 random sequences,  834 random matches,  6 NTs, cWW-L-L-cWW
Group 336, IL_81731.1  has acceptance rules -11.6226 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-11.6226 - AlignmentScore) +   3.0000 * CoreEdit <=  20.4444, method  8,TP   100.00%, TN    98.05%, min    98.05%,   1 3D sequences,     0 alignment sequences,   205 random sequences,    4 random matches, 17 NTs, cWW-cWW-L-R-L-R-L-cWW-L-tWW-L-R-L
Group 337, IL_81831.1  has acceptance rules  -4.8112 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.8112 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    78.74%, min    78.74%,   2 3D sequences,     0 alignment sequences, 10049 random sequences, 2136 random matches,  5 NTs, cWW-L-cWW
Group 338, IL_82107.4  has acceptance rules  -4.4918 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.4918 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    78.62%, min    78.62%,  30 3D sequences,     0 alignment sequences,  8714 random sequences, 1863 random matches,  4 NTs, cWW-cWW
Group 339, IL_82292.1  has acceptance rules -10.2013 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-10.2013 - AlignmentScore) +   3.0000 * CoreEdit <=  16.6461, method  6,TP   100.00%, TN    96.00%, min    96.00%,   3 3D sequences,     0 alignment sequences,  9404 random sequences,  376 random matches, 12 NTs, cWW-L-R-L-R-L-R-L-R-cWW
Group 340, IL_82426.6  has acceptance rules  -5.7415 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.7415 - AlignmentScore) +   3.0000 * CoreEdit <=  21.6619, method  8,TP   100.00%, TN    97.53%, min    97.53%,   6 3D sequences,     0 alignment sequences,    81 random sequences,    2 random matches, 14 NTs, cWW-cHW-R-L-cHW-cHW-cHW-L-cWW-R
Group 341, IL_82683.2  has acceptance rules  -3.2651 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.2651 - AlignmentScore) +   3.0000 * CoreEdit <=  17.3417, method  6,TP   100.00%, TN    96.00%, min    96.00%,  11 3D sequences,     0 alignment sequences,  7447 random sequences,  298 random matches,  8 NTs, cWW-L-R-L-cWW-L
Group 342, IL_82706.1  has acceptance rules  -5.9736 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.9736 - AlignmentScore) +   3.0000 * CoreEdit <=  18.5645, method  6,TP   100.00%, TN    95.99%, min    95.99%,   2 3D sequences,     0 alignment sequences, 12088 random sequences,  485 random matches,  7 NTs, cWW-L-R-L-cWW
Group 343, IL_82741.2  has acceptance rules  -5.8801 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.8801 - AlignmentScore) +   3.0000 * CoreEdit <=   9.9935, method  6,TP   100.00%, TN    96.00%, min    96.00%,   3 3D sequences,     0 alignment sequences, 14085 random sequences,  563 random matches,  7 NTs, cWW-L-cWW-L-L
Group 344, IL_82968.1  has acceptance rules  -6.3500 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.3500 - AlignmentScore) +   3.0000 * CoreEdit <=  18.2527, method  6,TP   100.00%, TN    95.99%, min    95.99%,   2 3D sequences,     0 alignment sequences,  6763 random sequences,  271 random matches, 11 NTs, cWW-L-cWW-L-L-R-L-R-L
Group 345, IL_83149.1  has acceptance rules -14.6354 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-14.6354 - AlignmentScore) +   3.0000 * CoreEdit <=  25.0000, method 12,TP   100.00%, TN      NaN%, min   100.00%,   2 3D sequences,     0 alignment sequences,     0 random sequences,    0 random matches, 24 NTs, cWW-tSH-tHH-L-R-L-R-L-R-L-R-L-R-L-R-L-cWW-L-cWW
Group 346, IL_83150.2  has acceptance rules  -5.8464 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.8464 - AlignmentScore) +   3.0000 * CoreEdit <=   9.7279, method  6,TP   100.00%, TN    95.98%, min    95.98%,   4 3D sequences,     0 alignment sequences,  7257 random sequences,  292 random matches,  7 NTs, cWW-tHH-cWW-L-L
Group 347, IL_83389.2  has acceptance rules  -5.7185 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.7185 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    90.10%, min    90.10%,   5 3D sequences,     0 alignment sequences, 10968 random sequences, 1086 random matches,  4 NTs, cWW-cWW
Group 348, IL_84251.1  has acceptance rules  -6.9051 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.9051 - AlignmentScore) +   3.0000 * CoreEdit <=  10.5579, method  6,TP   100.00%, TN    95.99%, min    95.99%,   2 3D sequences,     0 alignment sequences,  9519 random sequences,  382 random matches,  8 NTs, cWW-L-tHS-cWW
Group 349, IL_84409.1  has acceptance rules -14.6431 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-14.6431 - AlignmentScore) +   3.0000 * CoreEdit <=  25.0000, method 12,TP   100.00%, TN      NaN%, min   100.00%,   1 3D sequences,     0 alignment sequences,     0 random sequences,    0 random matches, 23 NTs, cWW-tSS-L-cWH-L-cSH-cHW-tWH-cSS-tWH-tSW-cWS-R-L-R-cSH-R-cWW-L
Group 350, IL_84476.1  has acceptance rules  -4.2784 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.2784 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    90.37%, min    90.37%,  13 3D sequences,     0 alignment sequences, 11584 random sequences, 1116 random matches,  4 NTs, cWW-cWW
Group 351, IL_84665.1  has acceptance rules -10.8969 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-10.8969 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    96.57%, min    96.57%,   1 3D sequences,     0 alignment sequences,  1398 random sequences,   48 random matches, 15 NTs, cWW-L-cSW-cWW-L-L-R-L-R-L-R-L
Group 352, IL_84694.2  has acceptance rules  -9.8383 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.8383 - AlignmentScore) +   3.0000 * CoreEdit <=  21.6313, method  8,TP   100.00%, TN    98.11%, min    98.11%,   3 3D sequences,     0 alignment sequences,   317 random sequences,    6 random matches, 16 NTs, cWW-L-R-tSH-tHW-tHH-tHS-cWW-cWW
Group 353, IL_85033.2  has acceptance rules  -6.3446 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.3446 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    89.38%, min    89.38%,  35 3D sequences,     0 alignment sequences,  7747 random sequences,  823 random matches,  8 NTs, cWW-cWW-cWW-cWW
Group 354, IL_85222.1  has acceptance rules  -8.7794 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.7794 - AlignmentScore) +   3.0000 * CoreEdit <=  19.1021, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences,  7418 random sequences,  297 random matches, 11 NTs, cWW-L-R-L-R-L-cWW-L-L
Group 355, IL_85498.1  has acceptance rules  -8.5936 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.5936 - AlignmentScore) +   3.0000 * CoreEdit <=  19.6601, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences,  4753 random sequences,  190 random matches, 12 NTs, cWW-L-R-L-cWW-L-L-R-L-R
Group 356, IL_85536.2  has acceptance rules  -8.9304 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.9304 - AlignmentScore) +   3.0000 * CoreEdit <=  16.1148, method  6,TP   100.00%, TN    96.00%, min    96.00%,   8 3D sequences,     0 alignment sequences,  5552 random sequences,  222 random matches, 12 NTs, cWW-tSH-L-R-tHS-cWW-cWW
Group 357, IL_85599.2  has acceptance rules  -4.8583 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.8583 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    90.20%, min    90.20%,   9 3D sequences,     0 alignment sequences,  6929 random sequences,  679 random matches,  6 NTs, cWW-tHS-cWW
Group 358, IL_85630.1  has acceptance rules  -9.5416 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.5416 - AlignmentScore) +   3.0000 * CoreEdit <=  22.0798, method  8,TP   100.00%, TN    97.94%, min    97.94%,   1 3D sequences,     0 alignment sequences,   631 random sequences,   13 random matches, 15 NTs, cWW-tSH-L-R-L-R-L-cWW-L-cWW-L
Group 359, IL_85652.1  has acceptance rules  -7.5971 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.5971 - AlignmentScore) +   3.0000 * CoreEdit <=  19.0856, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences,  6253 random sequences,  250 random matches, 12 NTs, cWW-tSH-L-R-L-R-L-cWW-L
Group 360, IL_85879.1  has acceptance rules -10.7851 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-10.7851 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    98.21%, min    98.21%,   1 3D sequences,     0 alignment sequences,    56 random sequences,    1 random matches, 16 NTs, cWW-L-R-tHW-tHW-L-R-L-R-cWW-cWW
Group 361, IL_86012.1  has acceptance rules  -8.2480 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.2480 - AlignmentScore) +   3.0000 * CoreEdit <=  24.6710, method  8,TP   100.00%, TN    97.75%, min    97.75%,   1 3D sequences,     0 alignment sequences,    89 random sequences,    2 random matches, 13 NTs, cWW-tHS-tWH-cWH-cWW-L-L-cWW
Group 362, IL_86136.1  has acceptance rules  -6.5775 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.5775 - AlignmentScore) +   3.0000 * CoreEdit <=  17.9693, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences,  8869 random sequences,  355 random matches, 11 NTs, cWW-tSH-L-cWW-L-L-R-L
Group 363, IL_87211.1  has acceptance rules  -4.7096 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.7096 - AlignmentScore) +   3.0000 * CoreEdit <=  13.4169, method  6,TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences,  9875 random sequences,  396 random matches,  7 NTs, cWW-cSW-L-cWW-L
Group 364, IL_87284.1  has acceptance rules  -9.0745 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.0745 - AlignmentScore) +   3.0000 * CoreEdit <=  15.9520, method  6,TP   100.00%, TN    95.99%, min    95.99%,   3 3D sequences,     0 alignment sequences,  3393 random sequences,  136 random matches, 12 NTs, cWW-tSH-tHW-tWH-tHS-cWW
Group 365, IL_87290.1  has acceptance rules -13.4677 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-13.4677 - AlignmentScore) +   3.0000 * CoreEdit <=  25.0000, method  1,TP   100.00%, TN    94.74%, min    94.74%,   1 3D sequences,     0 alignment sequences,    19 random sequences,    1 random matches, 15 NTs, cWW-L-R-L-R-L-R-L-R-L-R-L-R-L-R-L
Group 366, IL_87907.2  has acceptance rules  -3.7634 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.7634 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    89.51%, min    89.51%, 179 3D sequences,     0 alignment sequences,  4765 random sequences,  500 random matches,  6 NTs, cWW-cWW-cWW
Group 367, IL_88017.1  has acceptance rules  -2.6289 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -2.6289 - AlignmentScore) +   3.0000 * CoreEdit <=  15.8637, method  6,TP   100.00%, TN    95.98%, min    95.98%,   7 3D sequences,     0 alignment sequences,  5070 random sequences,  204 random matches,  9 NTs, cWW-L-cWW-L-L-R-L
Group 368, IL_88072.1  has acceptance rules  -6.9414 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.9414 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.68%, min    97.68%,   1 3D sequences,     0 alignment sequences,  1807 random sequences,   42 random matches, 13 NTs, cWW-L-R-L-cWW-L-L-R-L-R-L
Group 369, IL_88082.1  has acceptance rules  -6.5137 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.5137 - AlignmentScore) +   3.0000 * CoreEdit <=  15.6958, method  6,TP   100.00%, TN    95.96%, min    95.96%,   2 3D sequences,     0 alignment sequences, 13272 random sequences,  536 random matches,  8 NTs, cWW-L-tSS-L-cWW-L
Group 370, IL_88116.2  has acceptance rules  -8.5392 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.5392 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    96.27%, min    96.27%,   3 3D sequences,     0 alignment sequences,  3375 random sequences,  126 random matches, 14 NTs, cWW-tSH-L-R-L-R-L-R-cWW-cWW
Group 371, IL_88269.4  has acceptance rules  -7.6416 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.6416 - AlignmentScore) +   3.0000 * CoreEdit <=  17.7157, method  6,TP   100.00%, TN    96.00%, min    96.00%,   3 3D sequences,     0 alignment sequences,  7223 random sequences,  289 random matches, 11 NTs, cWW-tWW-cSH-tWH-tHS-cWW
Group 372, IL_88974.1  has acceptance rules  -7.2458 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.2458 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.48%, min    97.48%,   2 3D sequences,     0 alignment sequences,  3216 random sequences,   81 random matches, 12 NTs, cWW-L-R-L-cWW-L-L-R-L-R
Group 373, IL_89021.2  has acceptance rules  -6.0068 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.0068 - AlignmentScore) +   3.0000 * CoreEdit <=  12.6325, method  6,TP   100.00%, TN    96.00%, min    96.00%,   6 3D sequences,     0 alignment sequences,  5975 random sequences,  239 random matches, 10 NTs, cWW-L-R-L-R-tHS-cWW
Group 374, IL_89047.1  has acceptance rules  -9.7224 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.7224 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    98.08%, min    98.08%,   1 3D sequences,     0 alignment sequences,    52 random sequences,    1 random matches, 16 NTs, cWW-L-R-L-R-L-R-L-R-L-cWH-L-cWW
Group 375, IL_89099.1  has acceptance rules  -5.7275 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.7275 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    96.34%, min    96.34%,   1 3D sequences,     0 alignment sequences,  1638 random sequences,   60 random matches, 12 NTs, cWW-L-R-L-R-L-R-L-R-cWW
Group 376, IL_89312.1  has acceptance rules  -9.1602 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.1602 - AlignmentScore) +   3.0000 * CoreEdit <=  18.0804, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences,  5005 random sequences,  200 random matches, 10 NTs, cWW-tSH-L-cWS-cWW-L
Group 377, IL_89505.4  has acceptance rules  -2.1490 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -2.1490 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    93.34%, min    93.34%, 117 3D sequences,     0 alignment sequences,  4027 random sequences,  268 random matches,  5 NTs, cWW-L-cWW
Group 378, IL_89984.3  has acceptance rules  -5.0144 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.0144 - AlignmentScore) +   3.0000 * CoreEdit <=  12.5511, method  6,TP   100.00%, TN    95.96%, min    95.96%,   2 3D sequences,     0 alignment sequences, 13951 random sequences,  563 random matches,  7 NTs, cWW-L-R-L-cWW
Group 379, IL_90346.1  has acceptance rules  -6.9106 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.9106 - AlignmentScore) +   3.0000 * CoreEdit <=  15.2003, method  6,TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences, 16764 random sequences,  673 random matches,  9 NTs, cWW-L-R-L-cWW-L-L
Group 380, IL_90351.1  has acceptance rules  -5.5754 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.5754 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    92.33%, min    92.33%,   8 3D sequences,     0 alignment sequences, 11844 random sequences,  909 random matches,  7 NTs, cWW-L-R-L-cWW
Group 381, IL_90729.1  has acceptance rules  -3.2250 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.2250 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    93.17%, min    93.17%,  30 3D sequences,     0 alignment sequences,  5444 random sequences,  372 random matches,  5 NTs, cWW-L-cWW
Group 382, IL_91592.1  has acceptance rules  -6.1070 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.1070 - AlignmentScore) +   3.0000 * CoreEdit <=  16.9912, method  6,TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 10972 random sequences,  439 random matches, 10 NTs, cWW-L-tHH-L-cWW-L-L
Group 383, IL_91636.1  has acceptance rules  -5.4438 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.4438 - AlignmentScore) +   3.0000 * CoreEdit <=  19.7102, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences,  8115 random sequences,  325 random matches, 11 NTs, cWW-tSH-L-R-L-cWW-L-L
Group 384, IL_91698.1  has acceptance rules  -6.7285 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.7285 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.22%, min    97.22%,   2 3D sequences,     0 alignment sequences,    72 random sequences,    2 random matches, 17 NTs, cWW-tWW-L-R-L-R-L-R-L-tHW-R-L-cWW
Group 385, IL_91920.1  has acceptance rules  -4.6055 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.6055 - AlignmentScore) +   3.0000 * CoreEdit <=  15.4101, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences,  7647 random sequences,  306 random matches,  8 NTs, cWW-cWW-tHH-cWW
Group 386, IL_92446.2  has acceptance rules  -4.2259 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.2259 - AlignmentScore) +   3.0000 * CoreEdit <=  11.0492, method  6,TP   100.00%, TN    95.95%, min    95.95%,   5 3D sequences,     0 alignment sequences,  9283 random sequences,  376 random matches,  7 NTs, cWW-cWW-R-L-L
Group 387, IL_92634.2  has acceptance rules  -3.9771 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.9771 - AlignmentScore) +   3.0000 * CoreEdit <=  13.9534, method  6,TP   100.00%, TN    95.95%, min    95.95%,   3 3D sequences,     0 alignment sequences,  8817 random sequences,  357 random matches,  7 NTs, cWW-L-cWW-L-L
Group 388, IL_93889.1  has acceptance rules -11.3153 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-11.3153 - AlignmentScore) +   3.0000 * CoreEdit <=  25.0000, method  1,TP   100.00%, TN    66.67%, min    66.67%,   1 3D sequences,     0 alignment sequences,     3 random sequences,    1 random matches, 21 NTs, cWW-R-tSH-L-cSH-L-L-R-L-R-L-R-L-R-L-R-L-L
Group 389, IL_94351.1  has acceptance rules  -8.4815 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.4815 - AlignmentScore) +   3.0000 * CoreEdit <=  17.3420, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences,  7674 random sequences,  307 random matches, 11 NTs, cWW-L-R-L-R-L-tHS-cWW
Group 390, IL_94684.1  has acceptance rules  -3.6421 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.6421 - AlignmentScore) +   3.0000 * CoreEdit <=  15.2728, method  6,TP   100.00%, TN    96.01%, min    96.01%,   2 3D sequences,     0 alignment sequences,  6259 random sequences,  250 random matches,  9 NTs, cWW-tWH-R-L-cWW-L-L
Group 391, IL_94910.1  has acceptance rules  -7.1563 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.1563 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.39%, min    97.39%,   3 3D sequences,     0 alignment sequences,  1454 random sequences,   38 random matches, 12 NTs, cWW-tSS-tSH-L-R-R-L-cWW-L
Group 392, IL_94967.1  has acceptance rules  -5.2378 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.2378 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    95.15%, min    95.15%,   1 3D sequences,     0 alignment sequences, 12753 random sequences,  618 random matches,  6 NTs, cWW-L-cWW-L
Group 393, IL_95570.1  has acceptance rules  -6.3313 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.3313 - AlignmentScore) +   3.0000 * CoreEdit <=  12.8327, method  6,TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 13416 random sequences,  537 random matches,  7 NTs, cWW-cWH-R-L-cWW
Group 394, IL_95583.2  has acceptance rules  -3.8424 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.8424 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    89.79%, min    89.79%,  11 3D sequences,     0 alignment sequences,  8463 random sequences,  864 random matches,  5 NTs, cWW-L-cWW
Group 395, IL_95727.1  has acceptance rules  -9.5018 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.5018 - AlignmentScore) +   3.0000 * CoreEdit <=  20.1944, method  8,TP   100.00%, TN    97.98%, min    97.98%,   1 3D sequences,     0 alignment sequences,  1285 random sequences,   26 random matches, 14 NTs, cWW-L-tSH-L-tHW-tHS-R-cWW-L
Group 396, IL_95811.1  has acceptance rules  -5.7537 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.7537 - AlignmentScore) +   3.0000 * CoreEdit <=  19.4935, method  6,TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences,  5616 random sequences,  225 random matches, 11 NTs, cWW-L-cWW-L-cWW-L-R-L
Group 397, IL_96236.1  has acceptance rules  -5.4083 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.4083 - AlignmentScore) +   3.0000 * CoreEdit <=  16.9851, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences,  5430 random sequences,  217 random matches,  9 NTs, cWW-tWW-cWW-L-cWW
Group 398, IL_96303.1  has acceptance rules  -9.3544 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.3544 - AlignmentScore) +   3.0000 * CoreEdit <=  20.4884, method  8,TP   100.00%, TN    98.15%, min    98.15%,   3 3D sequences,     0 alignment sequences,   108 random sequences,    2 random matches, 13 NTs, cWW-cSH-tSW-tHW-cWW-L-L-R-L-R
Group 399, IL_96332.5  has acceptance rules  -6.8222 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.8222 - AlignmentScore) +   3.0000 * CoreEdit <=  17.0687, method  6,TP   100.00%, TN    96.00%, min    96.00%,   7 3D sequences,     0 alignment sequences, 11344 random sequences,  454 random matches, 10 NTs, cWW-cWW-L-R-L-cWW-L
Group 400, IL_96371.1  has acceptance rules  -4.2663 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.2663 - AlignmentScore) +   3.0000 * CoreEdit <=   9.8089, method  6,TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences,  9168 random sequences,  368 random matches,  6 NTs, cWW-tHH-cWW
Group 401, IL_96759.1  has acceptance rules  -4.8877 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.8877 - AlignmentScore) +   3.0000 * CoreEdit <=  11.6161, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences,  4574 random sequences,  183 random matches,  8 NTs, cWW-tSH-tWW-cWW
Group 402, IL_96788.1  has acceptance rules  -4.3375 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.3375 - AlignmentScore) +   3.0000 * CoreEdit <=  18.0541, method  6,TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences,  3718 random sequences,  149 random matches, 10 NTs, cWW-tHW-tHS-cWW-cWW
Group 403, IL_97273.1  has acceptance rules  -4.4505 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.4505 - AlignmentScore) +   3.0000 * CoreEdit <=  14.0402, method  6,TP   100.00%, TN    95.99%, min    95.99%,   3 3D sequences,     0 alignment sequences,  5413 random sequences,  217 random matches,  9 NTs, cWW-tSH-cWW-L-cWW-L
Group 404, IL_97631.1  has acceptance rules  -7.0325 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.0325 - AlignmentScore) +   3.0000 * CoreEdit <=  17.4438, method  6,TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences,  6367 random sequences,  255 random matches, 11 NTs, cWW-L-R-L-R-L-tHS-cWW
Group 405, IL_97697.1  has acceptance rules  -7.2338 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.2338 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.93%, min    97.93%,   4 3D sequences,     0 alignment sequences,  4978 random sequences,  103 random matches, 11 NTs, cWW-L-R-L-R-L-cWW-L-L
Group 406, IL_98347.1  has acceptance rules  -6.7492 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.7492 - AlignmentScore) +   3.0000 * CoreEdit <=  12.4544, method  6,TP   100.00%, TN    95.87%, min    95.87%,   1 3D sequences,     0 alignment sequences, 18346 random sequences,  757 random matches,  7 NTs, cWW-L-R-L-cWW
Group 407, IL_99358.1  has acceptance rules  -7.0427 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.0427 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    79.67%, min    79.67%,   8 3D sequences,     0 alignment sequences, 11721 random sequences, 2383 random matches,  7 NTs, cWW-L-R-L-cWW
Group 408, IL_99380.1  has acceptance rules  -4.8115 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.8115 - AlignmentScore) +   3.0000 * CoreEdit <=  14.4500, method  6,TP   100.00%, TN    95.77%, min    95.77%,   1 3D sequences,     0 alignment sequences,  9923 random sequences,  420 random matches,  8 NTs, cWW-L-cWW-L-L-R
Group 409, IL_99498.1  has acceptance rules  -8.1525 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.1525 - AlignmentScore) +   3.0000 * CoreEdit <=  16.9445, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences,  9685 random sequences,  387 random matches,  8 NTs, cWW-L-R-tHW-cWW
Group 410, IL_99646.2  has acceptance rules  -6.5247 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.5247 - AlignmentScore) +   3.0000 * CoreEdit <=  10.7376, method  6,TP   100.00%, TN    96.00%, min    96.00%,   6 3D sequences,     0 alignment sequences,  9508 random sequences,  380 random matches,  8 NTs, cWW-tWH-tHS-cWW
Group 411, IL_99692.2  has acceptance rules  -7.8108 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.8108 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.57%, min    97.57%,   6 3D sequences,     0 alignment sequences,  1728 random sequences,   42 random matches, 13 NTs, cWW-tSS-tSH-L-R-R-L-cWW-L-L
