
ans = 

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

               MotifID: 'HL_00317.1'
             Signature: {'cWW-F-cSS-F-F-F-F-F-F-F-F-F-F-F-F-F-F'}
                 NumNT: 19
          NumBasepairs: 2
            Structured: 1
             NumStacks: 14
                NumBPh: 0
                 NumBR: 0
          NumInstances: 1
              Truncate: [0×1 double]
              NumFixed: 46
              OwnScore: -15.1580
           OwnSequence: {'UGGCCUUUCUUAAAAAAAAA'}
          DeficitCoeff: 1
         CoreEditCoeff: 3
       SequenceLengths: 20
    MeanSequenceLength: 20
       DeficitEditData: [5×2 double]

1 sequences from 3D structures
Using 5 random sequences, 0 from an alignment, and 1 from 3D structures
Group   1, HL_00317.1  has acceptance rules AlignmentScore >= -35.1580, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  40.1580
TP   100.00%, TN    80.00%, min    80.00%,   1 3D sequences,     0 alignment sequences,    5 random sequences,    1 random matches, 19 NTs, cWW-F-cSS-F-F-F-F-F-F-F-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  80.00%, Minimum  80.00% 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: 'HL_00914.1'
                     Signature: {'cWW-F-F-F-F'}
                         NumNT: 6
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 2
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: -5.4881
                   OwnSequence: {'GGUCAAAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 8
            MeanSequenceLength: 8
               DeficitEditData: [5986×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 5986 random sequences, 0 from an alignment, and 1 from 3D structures
Group   2, HL_00914.1  has acceptance rules AlignmentScore >= -25.4881, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.6854
TP   100.00%, TN    95.84%, min    95.84%,   1 3D sequences,     0 alignment sequences, 5984 random sequences,  249 random matches,  6 NTs, cWW-F-F-F-F
Sensitivity 100.00%, Specificity  95.84%, Minimum  95.84% using method 6
Number of false positives with core edit > 0 is 249
1 * Deficit + 3 * Core Edit <= 11.1972
Motif index 1


ans = 

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

                       MotifID: 'HL_01255.1'
                     Signature: {'F-F-F-F-F-F-F-F'}
                         NumNT: 8
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 24
                      OwnScore: -8.3341
                   OwnSequence: {'CAUCCAGUAAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 12
            MeanSequenceLength: 12
               DeficitEditData: [1452×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 1452 random sequences, 0 from an alignment, and 1 from 3D structures
Group   3, HL_01255.1  has acceptance rules AlignmentScore >= -28.3341, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.1557
TP   100.00%, TN    95.94%, min    95.94%,   1 3D sequences,     0 alignment sequences, 1452 random sequences,   59 random matches,  8 NTs, F-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.94%, Minimum  95.94% using method 6
Number of false positives with core edit > 0 is 59
1 * Deficit + 3 * Core Edit <= 17.8216
Motif index 1


ans = 

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

                       MotifID: 'HL_01609.3'
                     Signature: {'cWW-tWH-F-F-F'}
                         NumNT: 7
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 18
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: [-6.0310 -6.0310 -5.8346 -5.6729 -5.6729 -4.7594 -8.6596 -6.6284 -5.6729 -6.0310 -5.6729 -5.6729 -6.3688 … ]
                   OwnSequence: {1×18 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8 8 9 9 8 8 9 9 8 9 9 8 8 8 9 9 9]
            MeanSequenceLength: 8.5000
               DeficitEditData: [5879×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

18 sequences from 3D structures
Using 5879 random sequences, 0 from an alignment, and 18 from 3D structures
Group   4, HL_01609.3  has acceptance rules AlignmentScore >= -24.7594, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.2738
TP   100.00%, TN    96.00%, min    96.00%,  18 3D sequences,     0 alignment sequences, 5875 random sequences,  235 random matches,  7 NTs, cWW-tWH-F-F-F
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 <= 12.5144
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: 'HL_01962.2'
                     Signature: {'cWW-tWH-tWH-F'}
                         NumNT: 7
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 6
                      Truncate: [0×1 double]
                      NumFixed: 14
                      OwnScore: [-6.6529 -7.8910 -8.2957 -7.2719 -7.6703 -7.6703]
                   OwnSequence: {'UUUAUUAAAAA'  'UUUACCAAAAA'  'UCUAGUAACAA'  'UUUAUCAAAAA'  'UCUAAUUAAAA'  'UCUAAUUAAAA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11 11 11 11 11]
            MeanSequenceLength: 11
               DeficitEditData: [3391×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

6 sequences from 3D structures
Using 3391 random sequences, 0 from an alignment, and 6 from 3D structures
Group   5, HL_01962.2  has acceptance rules AlignmentScore >= -26.6529, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  23.5219
TP   100.00%, TN    95.99%, min    95.99%,   6 3D sequences,     0 alignment sequences, 3391 random sequences,  136 random matches,  7 NTs, cWW-tWH-tWH-F
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 <= 16.8691
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: 'HL_02483.1'
                     Signature: {'cWW-tWH-F-cSH-F-F-F'}
                         NumNT: 10
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 24
                      OwnScore: -7.7782
                   OwnSequence: {'UGAUCACGAAGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 12
            MeanSequenceLength: 12
               DeficitEditData: [1680×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 1680 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  20.2106 because the cutoff seemed overly generous
Group   6, HL_02483.1  has acceptance rules AlignmentScore >= -27.7782, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  27.7782
TP   100.00%, TN    96.31%, min    96.31%,   1 3D sequences,     0 alignment sequences, 1680 random sequences,   62 random matches, 10 NTs, cWW-tWH-F-cSH-F-F-F
Sensitivity 100.00%, Specificity  96.31%, Minimum  96.31% using method 8
Number of false positives with core edit > 0 is 62
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: 'HL_02581.1'
                     Signature: {'cWW-tSH-cWS-tSW-F-F-F'}
                         NumNT: 11
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 20
                      OwnScore: [-9.5501 -9.5274]
                   OwnSequence: {'CGAGCCUGGUCAAAG'  'CAAGCCUGGCCAAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [15 15]
            MeanSequenceLength: 15
               DeficitEditData: [119×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 119 random sequences, 0 from an alignment, and 2 from 3D structures
Decreased cutoff from  20.5876 because the cutoff seemed overly generous
Group   7, HL_02581.1  has acceptance rules AlignmentScore >= -29.5274, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  29.5743
TP   100.00%, TN    98.32%, min    98.32%,   2 3D sequences,     0 alignment sequences,  119 random sequences,    2 random matches, 11 NTs, cWW-tSH-cWS-tSW-F-F-F
Sensitivity 100.00%, Specificity  98.32%, Minimum  98.32% using method 8
Number of false positives with core edit > 0 is 2
1 * Deficit + 3 * Core Edit <= 20.0469
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_02817.2'
                     Signature: {'cWW-F-F-F-F'}
                         NumNT: 6
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 3
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: [-4.7906 -4.7906 -7.0412]
                   OwnSequence: {'CCAAAUAG'  'CCAAAUAG'  'GAAUUAAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8 8]
            MeanSequenceLength: 8
               DeficitEditData: [5641×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 5641 random sequences, 0 from an alignment, and 3 from 3D structures
Group   8, HL_02817.2  has acceptance rules AlignmentScore >= -24.7906, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.7586
TP   100.00%, TN    95.99%, min    95.99%,   3 3D sequences,     0 alignment sequences, 5640 random sequences,  226 random matches,  6 NTs, cWW-F-F-F-F
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 226
1 * Deficit + 3 * Core Edit <= 11.9680
Motif index 1
Motif index 2
Motif index 3


ans = 

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

                       MotifID: 'HL_02887.3'
                     Signature: {'cWW-tWH-F-F-F-F-F-F'}
                         NumNT: 10
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 28
                      OwnScore: [-5.3391 -5.3391]
                   OwnSequence: {'CUGCAACCCG'  'CUGCAACUCG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10]
            MeanSequenceLength: 10
               DeficitEditData: [3123×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 3123 random sequences, 0 from an alignment, and 2 from 3D structures
Group   9, HL_02887.3  has acceptance rules AlignmentScore >= -25.3391, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.0341
TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 3123 random sequences,  125 random matches, 10 NTs, cWW-tWH-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 125
1 * Deficit + 3 * Core Edit <= 19.6950
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_04171.7'
                     Signature: {'cWW-cWW-F-F-F-F-F-F'}
                         NumNT: 10
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 9
                      Truncate: [0×1 double]
                      NumFixed: 28
                      OwnScore: [-5.2298 -5.2298 -5.2298 -5.2298 -5.2298 -5.2298 -5.2298 -6.3284 -9.8727]
                   OwnSequence: {1×9 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11 11 11 11 11 11 11 11]
            MeanSequenceLength: 11
               DeficitEditData: [2835×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

9 sequences from 3D structures
Using 2835 random sequences, 0 from an alignment, and 9 from 3D structures
Decreased cutoff from  21.1904 because the cutoff seemed overly generous
Group  10, HL_04171.7  has acceptance rules AlignmentScore >= -25.2298, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.2298
TP   100.00%, TN    97.78%, min    97.78%,   9 3D sequences,     0 alignment sequences, 2835 random sequences,   63 random matches, 10 NTs, cWW-cWW-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  97.78%, Minimum  97.78% using method 8
Number of false positives with core edit > 0 is 63
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


ans = 

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

                       MotifID: 'HL_04259.3'
                     Signature: {'cWW-F-F-F-F-F-F'}
                         NumNT: 8
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 7
                      Truncate: [0×1 double]
                      NumFixed: 22
                      OwnScore: [-6.5743 -7.1621 -7.5437 -8.3393 -6.7298 -9.8874 -8.4126]
                   OwnSequence: {'CCUACAAG'  'CCUGCAAG'  'CUGACACG'  'UAGAAAUA'  'UUGAAAAA'  'GCUUCAAAC'  'GGGGAACC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8 8 8 8 9 8]
            MeanSequenceLength: 8.1429
               DeficitEditData: [6813×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

7 sequences from 3D structures
Using 6813 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  11, HL_04259.3  has acceptance rules AlignmentScore >= -26.5743, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.0743
TP   100.00%, TN    95.72%, min    95.72%,   7 3D sequences,     0 alignment sequences, 6805 random sequences,  291 random matches,  8 NTs, cWW-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.72%, Minimum  95.72% using method 11
Number of false positives with core edit > 0 is 291
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: 'HL_04641.1'
                     Signature: {'cWW-F-F-F-F-F'}
                         NumNT: 7
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 2
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 22
                      OwnScore: -6.4541
                   OwnSequence: {'CAAGACGACG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 10
            MeanSequenceLength: 10
               DeficitEditData: [3522×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 3522 random sequences, 0 from an alignment, and 1 from 3D structures
Group  12, HL_04641.1  has acceptance rules AlignmentScore >= -26.4541, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  22.4785
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 3522 random sequences,  141 random matches,  7 NTs, cWW-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 141
1 * Deficit + 3 * Core Edit <= 16.0244
Motif index 1


ans = 

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

                       MotifID: 'HL_04642.1'
                     Signature: {'cWW-F-F-F-F-F'}
                         NumNT: 7
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 2
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 3
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: [-7.8711 -8.3820 -8.9636]
                   OwnSequence: {'CAGGCGGUUAG'  'CAGGUGGUUAG'  'CAGUCGGUAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11 10]
            MeanSequenceLength: 10.6667
               DeficitEditData: [3497×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 3497 random sequences, 0 from an alignment, and 3 from 3D structures
Group  13, HL_04642.1  has acceptance rules AlignmentScore >= -27.8711, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.8067
TP   100.00%, TN    96.00%, min    96.00%,   3 3D sequences,     0 alignment sequences, 3497 random sequences,  140 random matches,  7 NTs, cWW-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 140
1 * Deficit + 3 * Core Edit <= 17.9355
Motif index 1
Motif index 2
Motif index 3


ans = 

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

                       MotifID: 'HL_04725.1'
                     Signature: {'cWW-cWS-cWW-cWW-cWS'}
                         NumNT: 8
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 22
                      OwnScore: [-5.0288 -5.0288]
                   OwnSequence: {'GUUACUUAGUUC'  'GUUACUUAGUUC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [12 12]
            MeanSequenceLength: 12
               DeficitEditData: [783×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 783 random sequences, 0 from an alignment, and 2 from 3D structures
Decreased cutoff from  21.8554 because the cutoff seemed overly generous
Group  14, HL_04725.1  has acceptance rules AlignmentScore >= -25.0288, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.2544
TP   100.00%, TN    97.96%, min    97.96%,   2 3D sequences,     0 alignment sequences,  783 random sequences,   16 random matches,  8 NTs, cWW-cWS-cWW-cWW-cWS
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 <= 20.2255
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_04783.2'
                     Signature: {'cWW-F-F-F'}
                         NumNT: 5
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 9
                      Truncate: [0×1 double]
                      NumFixed: 12
                      OwnScore: [-6.0967 -6.1943 -7.7699 -9.1818 -11.5696 -12.5251 -8.2379 -9.7820 -6.8041]
                   OwnSequence: {'CGAAAG'  'GGAAAC'  'CUAGCG'  'GGAACAC'  'AUUGAAAAU'  'AUUGCAAAU'  'UGUAAG'  'CGCAACG'  'CGUAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 6 7 9 9 6 7 5]
            MeanSequenceLength: 6.7778
               DeficitEditData: [7815×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

9 sequences from 3D structures
Using 7815 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  15, HL_04783.2  has acceptance rules AlignmentScore >= -26.0967, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.5967
TP   100.00%, TN    81.03%, min    81.03%,   9 3D sequences,     0 alignment sequences, 7734 random sequences, 1467 random matches,  5 NTs, cWW-F-F-F
Sensitivity 100.00%, Specificity  81.03%, Minimum  81.03% using method 11
Number of false positives with core edit > 0 is 1467
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: 'HL_05304.3'
                     Signature: {'cWW-cWW-F-F-tSH-F-F-F-F-F'}
                         NumNT: 13
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 12
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 5
                      Truncate: [0×1 double]
                      NumFixed: 30
                      OwnScore: [-10.4004 -10.4004 -12.7691 -16.0549 -13.8658]
                   OwnSequence: {'AAUGUAAAUACCU'  'AAUGUAAAUACCU'  'GAGGUAGCGGUGC'  'GGUCAGAAAAUCUAC'  'AGGUUCGAAUCCU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [13 13 13 15 13]
            MeanSequenceLength: 13.4000
               DeficitEditData: [1534×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

5 sequences from 3D structures
Using 1534 random sequences, 0 from an alignment, and 5 from 3D structures
Group  16, HL_05304.3  has acceptance rules AlignmentScore >= -30.4004, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  29.7226
TP   100.00%, TN    96.02%, min    96.02%,   5 3D sequences,     0 alignment sequences, 1534 random sequences,   61 random matches, 13 NTs, cWW-cWW-F-F-tSH-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.02%, Minimum  96.02% using method 6
Number of false positives with core edit > 0 is 61
1 * Deficit + 3 * Core Edit <= 19.3222
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: 'HL_06059.6'
                     Signature: {'cWW-F-F-F-F-F-F-F'}
                         NumNT: 9
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 51
                      Truncate: [0×1 double]
                      NumFixed: 22
                      OwnScore: [-7.9220 -7.1198 -4.9266 -6.1570 -4.7484 -6.6176 -6.6176 -4.9266 -6.4333 -4.9266 -9.4949 -4.7484 -4.9266 … ]
                   OwnSequence: {1×51 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 10 9 9 9 9]
            MeanSequenceLength: 9.0196
               DeficitEditData: [3190×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

51 sequences from 3D structures
Using 3190 random sequences, 0 from an alignment, and 51 from 3D structures
Group  17, HL_06059.6  has acceptance rules AlignmentScore >= -24.7484, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  18.0609
TP    98.04%, TN    96.01%, min    96.01%,  51 3D sequences,     0 alignment sequences, 3186 random sequences,  127 random matches,  9 NTs, cWW-F-F-F-F-F-F-F
Sensitivity  98.04%, Specificity  96.01%, Minimum  96.01% using method 6
Number of false positives with core edit > 0 is 127
1 * Deficit + 3 * Core Edit <= 13.3125
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: 'HL_06226.4'
                     Signature: {'cWW-F-F-F-F-F-F-F'}
                         NumNT: 9
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 4
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: [-8.0798 -8.0798 -9.3812 -11.5693]
                   OwnSequence: {'CCUGAGAAACGG'  'CCUGAGAAACGG'  'GAUCAGAAUGC'  'GAUCAGCCAUGC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [12 12 11 12]
            MeanSequenceLength: 11.7500
               DeficitEditData: [2877×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 2877 random sequences, 0 from an alignment, and 4 from 3D structures
Group  18, HL_06226.4  has acceptance rules AlignmentScore >= -28.0798, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  27.8564
TP   100.00%, TN    96.00%, min    96.00%,   4 3D sequences,     0 alignment sequences, 2877 random sequences,  115 random matches,  9 NTs, cWW-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 115
1 * Deficit + 3 * Core Edit <= 19.7766
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: 'HL_07480.2'
                     Signature: {'cWW-tSH-F-F-F'}
                         NumNT: 7
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 3
                      Truncate: [0×1 double]
                      NumFixed: 16
                      OwnScore: [-7.2433 -7.2433 -7.2433]
                   OwnSequence: {'AAAGCGGUUAU'  'AAAGCGGUUAU'  'AAAGCGGUUAU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11 11]
            MeanSequenceLength: 11
               DeficitEditData: [930×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 930 random sequences, 0 from an alignment, and 3 from 3D structures
Group  19, HL_07480.2  has acceptance rules AlignmentScore >= -27.2433, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.0329
TP   100.00%, TN    96.02%, min    96.02%,   3 3D sequences,     0 alignment sequences,  930 random sequences,   37 random matches,  7 NTs, cWW-tSH-F-F-F
Sensitivity 100.00%, Specificity  96.02%, Minimum  96.02% using method 6
Number of false positives with core edit > 0 is 37
1 * Deficit + 3 * Core Edit <= 18.7897
Motif index 1
Motif index 2
Motif index 3


ans = 

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

                       MotifID: 'HL_07583.1'
                     Signature: {'cWW-cWW-F-F-F-F-F-F-F-F'}
                         NumNT: 12
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 13
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 34
                      OwnScore: [-15.1298 -13.2273]
                   OwnSequence: {'UGGAAUUGGUAGACA'  'AUUAAUACGGUUU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [15 13]
            MeanSequenceLength: 14
               DeficitEditData: [805×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 805 random sequences, 0 from an alignment, and 2 from 3D structures
Group  20, HL_07583.1  has acceptance rules AlignmentScore >= -33.2273, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  28.2057
TP   100.00%, TN    96.02%, min    96.02%,   2 3D sequences,     0 alignment sequences,  805 random sequences,   32 random matches, 12 NTs, cWW-cWW-F-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.02%, Minimum  96.02% using method 6
Number of false positives with core edit > 0 is 32
1 * Deficit + 3 * Core Edit <= 14.9784
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_07886.3'
                     Signature: {'cWW-F-F-F'}
                         NumNT: 5
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 6
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: [-6.8319 -6.8319 -9.6232 -10.3675 -5.4345 -5.4345]
                   OwnSequence: {'CGGAAAGG'  'CGGAAAGG'  'GAUAUGGC'  'AUUUU'  'UGAAGGA'  'UGAAGGA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8 8 5 7 7]
            MeanSequenceLength: 7.1667
               DeficitEditData: [7300×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

6 sequences from 3D structures
Using 7300 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  21, HL_07886.3  has acceptance rules AlignmentScore >= -25.4345, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  14.9345
TP   100.00%, TN    87.83%, min    87.83%,   6 3D sequences,     0 alignment sequences, 7264 random sequences,  884 random matches,  5 NTs, cWW-F-F-F
Sensitivity 100.00%, Specificity  87.83%, Minimum  87.83% using method 11
Number of false positives with core edit > 0 is 884
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: 'HL_07903.1'
                     Signature: {'cWW-cWW-F-F-F-F-F-F-F-F-F'}
                         NumNT: 13
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 32
                      OwnScore: -9.1715
                   OwnSequence: {'GUAUUGCAGUACCUC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 15
            MeanSequenceLength: 15
               DeficitEditData: [68×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 68 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  22.1855 because the cutoff seemed overly generous
Group  22, HL_07903.1  has acceptance rules AlignmentScore >= -29.1715, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  29.1715
TP   100.00%, TN    97.06%, min    97.06%,   1 3D sequences,     0 alignment sequences,   68 random sequences,    2 random matches, 13 NTs, cWW-cWW-F-F-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  97.06%, Minimum  97.06% 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: 'HL_07951.3'
                     Signature: {'cWW-F-F'}
                         NumNT: 4
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 2
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 4
                      Truncate: [0×1 double]
                      NumFixed: 12
                      OwnScore: [-10.0436 -9.7335 -13.7576 -14.3061]
                   OwnSequence: {'CAGCGGAAG'  'CAGCGGGAG'  'CAGCUGGUUAG'  'UCAUCUCCAA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 11 10]
            MeanSequenceLength: 9.7500
               DeficitEditData: [4058×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 4058 random sequences, 0 from an alignment, and 4 from 3D structures
Group  23, HL_07951.3  has acceptance rules AlignmentScore >= -29.7335, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  22.0094
TP   100.00%, TN    96.01%, min    96.01%,   4 3D sequences,     0 alignment sequences, 4058 random sequences,  162 random matches,  4 NTs, cWW-F-F
Sensitivity 100.00%, Specificity  96.01%, Minimum  96.01% using method 6
Number of false positives with core edit > 0 is 162
1 * Deficit + 3 * Core Edit <= 12.2759
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: 'HL_08100.1'
                     Signature: {'cWW-F-F-F'}
                         NumNT: 5
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 4
                      Truncate: [0×1 double]
                      NumFixed: 12
                      OwnScore: [-5.9430 -5.0957 -5.3428 -6.4601]
                   OwnSequence: {'CCUCGCG'  'CCUUGUG'  'CUUUAAG'  'CUUUUGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 7 7 7]
            MeanSequenceLength: 7
               DeficitEditData: [6335×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 6335 random sequences, 0 from an alignment, and 4 from 3D structures
Group  24, HL_08100.1  has acceptance rules AlignmentScore >= -25.0957, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.1799
TP   100.00%, TN    96.00%, min    96.00%,   4 3D sequences,     0 alignment sequences, 6329 random sequences,  253 random matches,  5 NTs, cWW-F-F-F
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 253
1 * Deficit + 3 * Core Edit <= 10.0841
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: 'HL_08510.1'
                     Signature: {'cWW-F-F-cSH-F-F'}
                         NumNT: 8
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: [-5.3349 -5.3349]
                   OwnSequence: {'AUGUGCUUU'  'AUGUGCUUU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9]
            MeanSequenceLength: 9
               DeficitEditData: [2325×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 2325 random sequences, 0 from an alignment, and 2 from 3D structures
Group  25, HL_08510.1  has acceptance rules AlignmentScore >= -25.3349, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  22.4866
TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 2325 random sequences,   93 random matches,  8 NTs, cWW-F-F-cSH-F-F
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 93
1 * Deficit + 3 * Core Edit <= 17.1518
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_08602.1'
                     Signature: {'cWW-cSS-F-cSS-F-F-F-F-F'}
                         NumNT: 11
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 2
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 32
                      OwnScore: -9.3260
                   OwnSequence: {'CAAUCCGCUCUAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 13
            MeanSequenceLength: 13
               DeficitEditData: [352×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 352 random sequences, 0 from an alignment, and 1 from 3D structures
Group  26, HL_08602.1  has acceptance rules AlignmentScore >= -29.3260, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  28.4028
TP   100.00%, TN    96.02%, min    96.02%,   1 3D sequences,     0 alignment sequences,  352 random sequences,   14 random matches, 11 NTs, cWW-cSS-F-cSS-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.02%, Minimum  96.02% using method 6
Number of false positives with core edit > 0 is 14
1 * Deficit + 3 * Core Edit <= 19.0768
Motif index 1


ans = 

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

                       MotifID: 'HL_09260.2'
                     Signature: {'cWW-F-F-F-F'}
                         NumNT: 6
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 2
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 3
                      Truncate: [0×1 double]
                      NumFixed: 16
                      OwnScore: [-10.2392 -10.2825 -11.7825]
                   OwnSequence: {'CAGCCUGGGAG'  'UAGCCUGGUUAG'  'UAGCCAGGUCAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 12 12]
            MeanSequenceLength: 11.6667
               DeficitEditData: [1170×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 1170 random sequences, 0 from an alignment, and 3 from 3D structures
Group  27, HL_09260.2  has acceptance rules AlignmentScore >= -30.2392, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.9294
TP   100.00%, TN    95.98%, min    95.98%,   3 3D sequences,     0 alignment sequences, 1170 random sequences,   47 random matches,  6 NTs, cWW-F-F-F-F
Sensitivity 100.00%, Specificity  95.98%, Minimum  95.98% using method 6
Number of false positives with core edit > 0 is 47
1 * Deficit + 3 * Core Edit <= 16.6902
Motif index 1
Motif index 2
Motif index 3


ans = 

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

                       MotifID: 'HL_09452.1'
                     Signature: {'cWW-F-F-F'}
                         NumNT: 5
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 3
                      Truncate: [0×1 double]
                      NumFixed: 14
                      OwnScore: [-8.7143 -8.7143 -9.8381]
                   OwnSequence: {'UAGGGGCUA'  'UAGGGGCUA'  'GCUUAGGC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 8]
            MeanSequenceLength: 8.6667
               DeficitEditData: [4185×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 4185 random sequences, 0 from an alignment, and 3 from 3D structures
Group  28, HL_09452.1  has acceptance rules AlignmentScore >= -28.7143, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  20.3205
TP   100.00%, TN    96.01%, min    96.01%,   3 3D sequences,     0 alignment sequences, 4185 random sequences,  167 random matches,  5 NTs, cWW-F-F-F
Sensitivity 100.00%, Specificity  96.01%, Minimum  96.01% using method 6
Number of false positives with core edit > 0 is 167
1 * Deficit + 3 * Core Edit <= 11.6062
Motif index 1
Motif index 2
Motif index 3


ans = 

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

                       MotifID: 'HL_10453.3'
                     Signature: {'cWW-F-F-F-F-F'}
                         NumNT: 7
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 9
                      Truncate: [0×1 double]
                      NumFixed: 20
                      OwnScore: [-7.8040 -7.8040 -7.4005 -7.4005 -10.8196 -10.9076 -11.5120 -5.5959 -5.5959]
                   OwnSequence: {1×9 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 9 9 8 8 8 7 7]
            MeanSequenceLength: 8.2222
               DeficitEditData: [6726×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

9 sequences from 3D structures
Using 6726 random sequences, 0 from an alignment, and 9 from 3D structures
Group  29, HL_10453.3  has acceptance rules AlignmentScore >= -25.5959, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.6569
TP   100.00%, TN    96.00%, min    96.00%,   9 3D sequences,     0 alignment sequences, 6725 random sequences,  269 random matches,  7 NTs, cWW-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 269
1 * Deficit + 3 * Core Edit <= 11.0611
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: 'HL_10456.1'
                     Signature: {'cWW-F-cWW-tWW-F-tHW-F-F-F-F-F-F-F'}
                         NumNT: 17
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 12
                        NumBPh: 0
                         NumBR: 3
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 42
                      OwnScore: [-7.6384 -7.6384]
                   OwnSequence: {'CAUCAGGGGAGGAAUCGG'  'CAUCAGGGGAGGAAUCGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [18 18]
            MeanSequenceLength: 18
               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  30, HL_10456.1  has acceptance rules AlignmentScore >= -27.6384, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  32.6384
TP   100.00%, TN      NaN%, min   100.00%,   2 3D sequences,     0 alignment sequences,    0 random sequences,    0 random matches, 17 NTs, cWW-F-cWW-tWW-F-tHW-F-F-F-F-F-F-F
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: 'HL_10540.1'
                     Signature: {'cWW-F-F-F-F-F'}
                         NumNT: 7
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: [-7.2067 -8.3110]
                   OwnSequence: {'CCGAAGG'  'UGGCUAAAA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 9]
            MeanSequenceLength: 8
               DeficitEditData: [6646×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 6646 random sequences, 0 from an alignment, and 2 from 3D structures
Group  31, HL_10540.1  has acceptance rules AlignmentScore >= -27.2067, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.6019
TP   100.00%, TN    95.83%, min    95.83%,   2 3D sequences,     0 alignment sequences, 6645 random sequences,  277 random matches,  7 NTs, cWW-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.83%, Minimum  95.83% using method 6
Number of false positives with core edit > 0 is 277
1 * Deficit + 3 * Core Edit <= 10.3952
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_11542.1'
                     Signature: {'cWW-tSH-F-F-F-F-F-F'}
                         NumNT: 10
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 2
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 22
                      OwnScore: -9.5311
                   OwnSequence: {'CGAGCGGCCAAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 13
            MeanSequenceLength: 13
               DeficitEditData: [498×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 498 random sequences, 0 from an alignment, and 1 from 3D structures
Group  32, HL_11542.1  has acceptance rules AlignmentScore >= -29.5311, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  27.4905
TP   100.00%, TN    95.98%, min    95.98%,   1 3D sequences,     0 alignment sequences,  498 random sequences,   20 random matches, 10 NTs, cWW-tSH-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.98%, Minimum  95.98% using method 6
Number of false positives with core edit > 0 is 20
1 * Deficit + 3 * Core Edit <= 17.9595
Motif index 1


ans = 

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

                       MotifID: 'HL_12758.3'
                     Signature: {'cWW-tSH-F-cHW-F-F-cWH-cHW-cWH-cHW-cWH-cWH-F-tSH-F-cHW-F-cWH-cWH'}
                         NumNT: 19
                  NumBasepairs: 15
                    Structured: 1
                     NumStacks: 18
                        NumBPh: 1
                         NumBR: 2
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 54
                      OwnScore: [-13.9168 -10.6766]
                   OwnSequence: {'CGAAGGUGAGGAGAGGCGAGGAAGAG'  'CGAAGGGACGGUGCGGAGAGGAGAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [26 25]
            MeanSequenceLength: 25.5000
               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  33, HL_12758.3  has acceptance rules AlignmentScore >= -30.6766, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  35.6766
TP   100.00%, TN      NaN%, min   100.00%,   2 3D sequences,     0 alignment sequences,    0 random sequences,    0 random matches, 19 NTs, cWW-tSH-F-cHW-F-F-cWH-cHW-cWH-cHW-cWH-cWH-F-tSH-F-cHW-F-cWH-cWH
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: 'HL_12870.1'
                     Signature: {'cWW-tHW-F-F-F-F-F-F-F-F-F'}
                         NumNT: 12
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 32
                      OwnScore: -7.4651
                   OwnSequence: {'GUCCUUGGGAAAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 13
            MeanSequenceLength: 13
               DeficitEditData: [235×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 235 random sequences, 0 from an alignment, and 1 from 3D structures
Group  34, HL_12870.1  has acceptance rules AlignmentScore >= -27.4651, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.6155
TP   100.00%, TN    96.17%, min    96.17%,   1 3D sequences,     0 alignment sequences,  235 random sequences,    9 random matches, 12 NTs, cWW-tHW-F-F-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.17%, Minimum  96.17% using method 6
Number of false positives with core edit > 0 is 9
1 * Deficit + 3 * Core Edit <= 18.1504
Motif index 1


ans = 

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

                       MotifID: 'HL_13189.1'
                     Signature: {'cWW-F-F'}
                         NumNT: 4
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 2
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 12
                      OwnScore: [-7.2565 -5.8431]
                   OwnSequence: {'CCUCGG'  'UGUAA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 5]
            MeanSequenceLength: 5.5000
               DeficitEditData: [6355×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 6355 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  35, HL_13189.1  has acceptance rules AlignmentScore >= -25.8431, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.3431
TP   100.00%, TN    68.64%, min    68.64%,   2 3D sequences,     0 alignment sequences, 6332 random sequences, 1986 random matches,  4 NTs, cWW-F-F
Sensitivity 100.00%, Specificity  68.64%, Minimum  68.64% using method 11
Number of false positives with core edit > 0 is 1986
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: 'HL_13529.1'
                     Signature: {'cWW-F-F-F-F'}
                         NumNT: 7
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: [-6.4438 -6.6026]
                   OwnSequence: {'UUAACUG'  'GAAAAAAGC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 9]
            MeanSequenceLength: 8
               DeficitEditData: [7441×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 7441 random sequences, 0 from an alignment, and 2 from 3D structures
Group  36, HL_13529.1  has acceptance rules AlignmentScore >= -26.4438, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.9170
TP   100.00%, TN    95.97%, min    95.97%,   2 3D sequences,     0 alignment sequences, 7441 random sequences,  300 random matches,  7 NTs, cWW-F-F-F-F
Sensitivity 100.00%, Specificity  95.97%, Minimum  95.97% using method 6
Number of false positives with core edit > 0 is 300
1 * Deficit + 3 * Core Edit <= 11.4732
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_13963.3'
                     Signature: {'cWW-F-F'}
                         NumNT: 4
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 2
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 4
                      Truncate: [0×1 double]
                      NumFixed: 14
                      OwnScore: [-6.3650 -6.3650 -11.8186 -12.1310]
                   OwnSequence: {'GGCGAC'  'GGCGAC'  'GCCUAGGAC'  'GCUUAUGC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 9 8]
            MeanSequenceLength: 7.2500
               DeficitEditData: [7545×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 7545 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  37, HL_13963.3  has acceptance rules AlignmentScore >= -26.3650, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.8650
TP   100.00%, TN    92.41%, min    92.41%,   4 3D sequences,     0 alignment sequences, 7534 random sequences,  572 random matches,  4 NTs, cWW-F-F
Sensitivity 100.00%, Specificity  92.41%, Minimum  92.41% using method 11
Number of false positives with core edit > 0 is 572
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: 'HL_13971.1'
                     Signature: {'cWW-cWS-F-tSW-F-tSH-tSH-cWW-F-F'}
                         NumNT: 14
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 1
                         NumBR: 3
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 34
                      OwnScore: [-6.3144 -6.3144]
                   OwnSequence: {'UUCCCGUCCGAUCA'  'UCCCCGUUCGAUCA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [14 14]
            MeanSequenceLength: 14
               DeficitEditData: [17×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 17 random sequences, 0 from an alignment, and 2 from 3D structures
Group  38, HL_13971.1  has acceptance rules AlignmentScore >= -26.3144, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  31.3144
TP   100.00%, TN   100.00%, min   100.00%,   2 3D sequences,     0 alignment sequences,   17 random sequences,    0 random matches, 14 NTs, cWW-cWS-F-tSW-F-tSH-tSH-cWW-F-F
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


ans = 

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

                       MotifID: 'HL_14757.1'
                     Signature: {'cWW-cWW-F-F-tSW-tWW-cWW-tHW-tSW-F-cWH-F'}
                         NumNT: 17
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 16
                        NumBPh: 2
                         NumBR: 1
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 46
                      OwnScore: -8.5917
                   OwnSequence: {'CCUGACUUCUAUACUAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 18
            MeanSequenceLength: 18
               DeficitEditData: [18.9392 4]
              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  39, HL_14757.1  has acceptance rules AlignmentScore >= -28.5917, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  33.5917
TP   100.00%, TN   100.00%, min   100.00%,   1 3D sequences,     0 alignment sequences,    1 random sequences,    0 random matches, 17 NTs, cWW-cWW-F-F-tSW-tWW-cWW-tHW-tSW-F-cWH-F
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: 'HL_15118.1'
                     Signature: {'cWW-F-F-F-F-F-F-F-F-F'}
                         NumNT: 11
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 28
                      OwnScore: -8.5594
                   OwnSequence: {'CAUUGCACUCCG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 12
            MeanSequenceLength: 12
               DeficitEditData: [636×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 636 random sequences, 0 from an alignment, and 1 from 3D structures
Group  40, HL_15118.1  has acceptance rules AlignmentScore >= -28.5594, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  28.3197
TP   100.00%, TN    96.07%, min    96.07%,   1 3D sequences,     0 alignment sequences,  636 random sequences,   25 random matches, 11 NTs, cWW-F-F-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.07%, Minimum  96.07% using method 6
Number of false positives with core edit > 0 is 25
1 * Deficit + 3 * Core Edit <= 19.7603
Motif index 1


ans = 

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

                       MotifID: 'HL_15574.1'
                     Signature: {'cWW-F-F-F-F-F'}
                         NumNT: 7
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 20
                      OwnScore: [-5.1260 -5.8191]
                   OwnSequence: {'GAAACAC'  'GUAAAAGC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 8]
            MeanSequenceLength: 7.5000
               DeficitEditData: [5943×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 5943 random sequences, 0 from an alignment, and 2 from 3D structures
Group  41, HL_15574.1  has acceptance rules AlignmentScore >= -25.1260, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  14.7435
TP   100.00%, TN    95.55%, min    95.55%,   2 3D sequences,     0 alignment sequences, 5936 random sequences,  264 random matches,  7 NTs, cWW-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.55%, Minimum  95.55% using method 6
Number of false positives with core edit > 0 is 264
1 * Deficit + 3 * Core Edit <= 9.6176
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_15802.1'
                     Signature: {'cWW-cWW-F-F-F'}
                         NumNT: 7
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 16
                      OwnScore: -6.2013
                   OwnSequence: {'ACUCUGGAU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 9
            MeanSequenceLength: 9
               DeficitEditData: [4737×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 4737 random sequences, 0 from an alignment, and 1 from 3D structures
Group  42, HL_15802.1  has acceptance rules AlignmentScore >= -26.2013, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  22.1963
TP   100.00%, TN    96.01%, min    96.01%,   1 3D sequences,     0 alignment sequences, 4737 random sequences,  189 random matches,  7 NTs, cWW-cWW-F-F-F
Sensitivity 100.00%, Specificity  96.01%, Minimum  96.01% using method 6
Number of false positives with core edit > 0 is 189
1 * Deficit + 3 * Core Edit <= 15.9950
Motif index 1


ans = 

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

                       MotifID: 'HL_16398.2'
                     Signature: {'cWW-F-F-F-F-F-F'}
                         NumNT: 8
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 3
                      Truncate: [0×1 double]
                      NumFixed: 22
                      OwnScore: [-12.1502 -12.1502 -15.0444]
                   OwnSequence: {'GAAGAAUACGACC'  'GAAGAAUACGACC'  'GACCUAGAUCACCC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [13 13 14]
            MeanSequenceLength: 13.3333
               DeficitEditData: [984×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 984 random sequences, 0 from an alignment, and 3 from 3D structures
Group  43, HL_16398.2  has acceptance rules AlignmentScore >= -32.1502, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  29.2179
TP   100.00%, TN    96.04%, min    96.04%,   3 3D sequences,     0 alignment sequences,  984 random sequences,   39 random matches,  8 NTs, cWW-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.04%, Minimum  96.04% using method 6
Number of false positives with core edit > 0 is 39
1 * Deficit + 3 * Core Edit <= 17.0678
Motif index 1
Motif index 2
Motif index 3


ans = 

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

                       MotifID: 'HL_16991.1'
                     Signature: {'cWW-cWH-cWH-F-cWH-F'}
                         NumNT: 8
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 16
                      OwnScore: -6.4750
                   OwnSequence: {'UGUGGAGGAGUA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 12
            MeanSequenceLength: 12
               DeficitEditData: [1165×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 1165 random sequences, 0 from an alignment, and 1 from 3D structures
Group  44, HL_16991.1  has acceptance rules AlignmentScore >= -26.4750, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.9870
TP   100.00%, TN    95.97%, min    95.97%,   1 3D sequences,     0 alignment sequences, 1165 random sequences,   47 random matches,  8 NTs, cWW-cWH-cWH-F-cWH-F
Sensitivity 100.00%, Specificity  95.97%, Minimum  95.97% using method 6
Number of false positives with core edit > 0 is 47
1 * Deficit + 3 * Core Edit <= 19.5119
Motif index 1


ans = 

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

                       MotifID: 'HL_18423.1'
                     Signature: {'cWW-tSH-tHS-F'}
                         NumNT: 7
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 14
                      OwnScore: -9.2929
                   OwnSequence: {'UGAUCAAUGAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 11
            MeanSequenceLength: 11
               DeficitEditData: [3651×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 3651 random sequences, 0 from an alignment, and 1 from 3D structures
Group  45, HL_18423.1  has acceptance rules AlignmentScore >= -29.2929, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.8286
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 3651 random sequences,  146 random matches,  7 NTs, cWW-tSH-tHS-F
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 146
1 * Deficit + 3 * Core Edit <= 16.5357
Motif index 1


ans = 

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

                       MotifID: 'HL_18565.1'
                     Signature: {'cWW-cWW-F-F-F-F'}
                         NumNT: 8
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: [-5.6980 -5.1692]
                   OwnSequence: {'ACUGCAGAU'  'ACUGAAGAU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9]
            MeanSequenceLength: 9
               DeficitEditData: [5246×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 5246 random sequences, 0 from an alignment, and 2 from 3D structures
Group  46, HL_18565.1  has acceptance rules AlignmentScore >= -25.1692, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  21.7042
TP   100.00%, TN    95.96%, min    95.96%,   2 3D sequences,     0 alignment sequences, 5246 random sequences,  212 random matches,  8 NTs, cWW-cWW-F-F-F-F
Sensitivity 100.00%, Specificity  95.96%, Minimum  95.96% using method 6
Number of false positives with core edit > 0 is 212
1 * Deficit + 3 * Core Edit <= 16.5350
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_18978.1'
                     Signature: {'cWW-F-F-tHW-F-F-F'}
                         NumNT: 9
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: -6.1826
                   OwnSequence: {'CUGUUCGCAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 10
            MeanSequenceLength: 10
               DeficitEditData: [2798×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 2798 random sequences, 0 from an alignment, and 1 from 3D structures
Group  47, HL_18978.1  has acceptance rules AlignmentScore >= -26.1826, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.9535
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 2798 random sequences,  112 random matches,  9 NTs, cWW-F-F-tHW-F-F-F
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 112
1 * Deficit + 3 * Core Edit <= 18.7709
Motif index 1


ans = 

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

                       MotifID: 'HL_19210.3'
                     Signature: {'cWW-F-F-F-F-F-F-F-F'}
                         NumNT: 10
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 1
                         NumBR: 2
                  NumInstances: 7
                      Truncate: [0×1 double]
                      NumFixed: 26
                      OwnScore: [-4.8159 -4.8159 -4.8159 -4.8159 -6.8219 -6.8219 -9.6775]
                   OwnSequence: {'CUUAGAAGCAG'  'CUUAGAAGCAG'  'CUUAGAAGCAG'  'CUUAGAAGCAG'  'CAUGGAAGUCG'  'CAUGGAAGUCG'  'GUUCGAUUCC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11 11 11 11 11 10]
            MeanSequenceLength: 10.8571
               DeficitEditData: [1799×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

7 sequences from 3D structures
Using 1799 random sequences, 0 from an alignment, and 7 from 3D structures
Group  48, HL_19210.3  has acceptance rules AlignmentScore >= -24.8159, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  22.9005
TP   100.00%, TN    96.00%, min    96.00%,   7 3D sequences,     0 alignment sequences, 1798 random sequences,   72 random matches, 10 NTs, cWW-F-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 72
1 * Deficit + 3 * Core Edit <= 18.0846
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: 'HL_20167.2'
                     Signature: {'cWW-F-F-F-F-F-F'}
                         NumNT: 8
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 10
                      Truncate: [0×1 double]
                      NumFixed: 24
                      OwnScore: [-5.5702 -5.5702 -5.5702 -5.5702 -8.7108 -8.4749 -8.4749 -9.7446 -12.9830 -12.0369]
                   OwnSequence: {1×10 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 9 9 9 9 9 9 9 9]
            MeanSequenceLength: 9
               DeficitEditData: [7226×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

10 sequences from 3D structures
Using 7226 random sequences, 0 from an alignment, and 10 from 3D structures
Group  49, HL_20167.2  has acceptance rules AlignmentScore >= -25.5702, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  19.0081
TP   100.00%, TN    96.00%, min    96.00%,  10 3D sequences,     0 alignment sequences, 7224 random sequences,  289 random matches,  8 NTs, cWW-F-F-F-F-F-F
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 <= 13.4378
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: 'HL_20535.2'
                     Signature: {'cWW-F-F-F-F'}
                         NumNT: 6
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 2
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 3
                      Truncate: [0×1 double]
                      NumFixed: 20
                      OwnScore: [-10.5796 -11.1457 -10.4018]
                   OwnSequence: {'GAUAAUAC'  'UCCUUGUGG'  'GUUCGACUC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 9 9]
            MeanSequenceLength: 8.6667
               DeficitEditData: [8455×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 8455 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  50, HL_20535.2  has acceptance rules AlignmentScore >= -30.4018, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  19.9018
TP   100.00%, TN    94.69%, min    94.69%,   3 3D sequences,     0 alignment sequences, 8455 random sequences,  449 random matches,  6 NTs, cWW-F-F-F-F
Sensitivity 100.00%, Specificity  94.69%, Minimum  94.69% 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


ans = 

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

                       MotifID: 'HL_20743.5'
                     Signature: {'cWW-cWW-F-F-F-F'}
                         NumNT: 8
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 7
                      Truncate: [0×1 double]
                      NumFixed: 22
                      OwnScore: [-5.3669 -5.3669 -5.6828 -5.7675 -5.3669 -6.5865 -6.5865]
                   OwnSequence: {'GGAUAUGGC'  'GGAUAUGGC'  'GGAUAUAGC'  'AAAUAUGGU'  'GGAUAUGGC'  'CAUAAUGGG'  'CAUAAUGGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 9 9 9 9 9]
            MeanSequenceLength: 9
               DeficitEditData: [5297×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

7 sequences from 3D structures
Using 5297 random sequences, 0 from an alignment, and 7 from 3D structures
Group  51, HL_20743.5  has acceptance rules AlignmentScore >= -25.3669, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  20.3614
TP   100.00%, TN    96.00%, min    96.00%,   7 3D sequences,     0 alignment sequences, 5297 random sequences,  212 random matches,  8 NTs, cWW-cWW-F-F-F-F
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 <= 14.9945
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: 'HL_20751.2'
                     Signature: {'cWW-tHW-F-F-F-F-F-F-F-F-F'}
                         NumNT: 13
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 3
                      Truncate: [0×1 double]
                      NumFixed: 32
                      OwnScore: [-8.6242 -8.6242 -13.2439]
                   OwnSequence: {'CAGGGGAGGAAUCG'  'CAGGGGAGGAAUCG'  'GACGGGGAGUUGU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [14 14 13]
            MeanSequenceLength: 13.6667
               DeficitEditData: [324×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 324 random sequences, 0 from an alignment, and 3 from 3D structures
Group  52, HL_20751.2  has acceptance rules AlignmentScore >= -28.6242, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  27.9086
TP   100.00%, TN    95.99%, min    95.99%,   3 3D sequences,     0 alignment sequences,  324 random sequences,   13 random matches, 13 NTs, cWW-tHW-F-F-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 13
1 * Deficit + 3 * Core Edit <= 19.2844
Motif index 1
Motif index 2
Motif index 3


ans = 

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

                       MotifID: 'HL_20781.1'
                     Signature: {'cWW-F-F-F-F-F-F-F-F'}
                         NumNT: 10
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 26
                      OwnScore: -7.8663
                   OwnSequence: {'CAAAAAUGAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 11
            MeanSequenceLength: 11
               DeficitEditData: [2420×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 2420 random sequences, 0 from an alignment, and 1 from 3D structures
Group  53, HL_20781.1  has acceptance rules AlignmentScore >= -27.8663, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  21.4431
TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences, 2420 random sequences,   97 random matches, 10 NTs, cWW-F-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 97
1 * Deficit + 3 * Core Edit <= 13.5768
Motif index 1


ans = 

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

                       MotifID: 'HL_20811.4'
                     Signature: {'cWW-cWS-F'}
                         NumNT: 5
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 2
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 14
                      Truncate: [0×1 double]
                      NumFixed: 12
                      OwnScore: [-7.7674 -8.8660 -7.6562 -14.2679 -8.8660 -8.7095 -8.8660 -7.5199 -11.5253 -8.8660 -9.9646 -7.5199 … ]
                   OwnSequence: {1×14 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10 10 11 10 9 10 9 9 10 10 9 10 6]
            MeanSequenceLength: 9.5000
               DeficitEditData: [8148×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

14 sequences from 3D structures
Using 8148 random sequences, 0 from an alignment, and 14 from 3D structures
Group  54, HL_20811.4  has acceptance rules AlignmentScore >= -27.5199, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.9469
TP   100.00%, TN    96.00%, min    96.00%,  14 3D sequences,     0 alignment sequences, 8130 random sequences,  325 random matches,  5 NTs, cWW-cWS-F
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 <= 10.4270
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: 'HL_21372.1'
                     Signature: {'cWW-F-cSH-F-F'}
                         NumNT: 5
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 1
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 14
                      OwnScore: [-8.9177 -8.2538]
                   OwnSequence: {'UUUCGUGUG'  'AUUCGUAAU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9]
            MeanSequenceLength: 9
               DeficitEditData: [4607×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 4607 random sequences, 0 from an alignment, and 2 from 3D structures
Group  55, HL_21372.1  has acceptance rules AlignmentScore >= -28.2538, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  20.3725
TP   100.00%, TN    95.98%, min    95.98%,   2 3D sequences,     0 alignment sequences, 4607 random sequences,  185 random matches,  5 NTs, cWW-F-cSH-F-F
Sensitivity 100.00%, Specificity  95.98%, Minimum  95.98% using method 6
Number of false positives with core edit > 0 is 185
1 * Deficit + 3 * Core Edit <= 12.1187
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_21400.1'
                     Signature: {'cWW-tWH-tSW-cWW-cWH-cHW-cWH-cWH-cHW-cWH-cHW-cWH-cWH-cWH-cWH-cWH'}
                         NumNT: 18
                  NumBasepairs: 16
                    Structured: 1
                     NumStacks: 22
                        NumBPh: 2
                         NumBR: 2
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 48
                      OwnScore: -7.0896
                   OwnSequence: {'AGGUGGGUGGUGUGGAGGAGUAU'}
                  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  56, HL_21400.1  has acceptance rules AlignmentScore >= -27.0896, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  32.0896
TP   100.00%, TN      NaN%, min   100.00%,   1 3D sequences,     0 alignment sequences,    0 random sequences,    0 random matches, 18 NTs, cWW-tWH-tSW-cWW-cWH-cHW-cWH-cWH-cHW-cWH-cHW-cWH-cWH-cWH-cWH-cWH
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: 'HL_22135.1'
                     Signature: {'cWW-F-F'}
                         NumNT: 4
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 12
                      OwnScore: -3.2074
                   OwnSequence: {'UCCAA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 5
            MeanSequenceLength: 5
               DeficitEditData: [4809×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 4809 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  57, HL_22135.1  has acceptance rules AlignmentScore >= -23.2074, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  12.7074
TP   100.00%, TN    85.44%, min    85.44%,   1 3D sequences,     0 alignment sequences, 4801 random sequences,  699 random matches,  4 NTs, cWW-F-F
Sensitivity 100.00%, Specificity  85.44%, Minimum  85.44% using method 11
Number of false positives with core edit > 0 is 699
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: 'HL_22584.6'
                     Signature: {'cWW-tSW-F'}
                         NumNT: 5
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 26
                      Truncate: [0×1 double]
                      NumFixed: 12
                      OwnScore: [-2.3968 -2.3968 -2.3968 -2.3968 -2.3968 -2.3968 -2.3968 -2.3968 -2.3968 -2.3968 -2.3968 -2.3968 -2.3968 … ]
                   OwnSequence: {1×26 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 6 6]
            MeanSequenceLength: 6.9231
               DeficitEditData: [4313×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

26 sequences from 3D structures
Using 4313 random sequences, 0 from an alignment, and 26 from 3D structures
Group  58, HL_22584.6  has acceptance rules AlignmentScore >= -22.3968, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.6832
TP   100.00%, TN    96.01%, min    96.01%,  26 3D sequences,     0 alignment sequences, 4286 random sequences,  171 random matches,  5 NTs, cWW-tSW-F
Sensitivity 100.00%, Specificity  96.01%, Minimum  96.01% using method 6
Number of false positives with core edit > 0 is 171
1 * Deficit + 3 * Core Edit <= 11.2864
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


ans = 

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

                       MotifID: 'HL_22622.1'
                     Signature: {'cWW-F-F-F-F-F'}
                         NumNT: 6
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 16
                      OwnScore: [-9.0141 -7.4736]
                   OwnSequence: {'CGACGGUUG'  'CAUGGACG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 8]
            MeanSequenceLength: 8.5000
               DeficitEditData: [4588×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 4588 random sequences, 0 from an alignment, and 2 from 3D structures
Group  59, HL_22622.1  has acceptance rules AlignmentScore >= -27.4736, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  18.9841
TP   100.00%, TN    95.99%, min    95.99%,   2 3D sequences,     0 alignment sequences, 4588 random sequences,  184 random matches,  6 NTs, cWW-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 184
1 * Deficit + 3 * Core Edit <= 11.5105
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_23010.1'
                     Signature: {'cWW-F-F-F-F-F-F'}
                         NumNT: 8
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 20
                      OwnScore: -7.8097
                   OwnSequence: {'CAAGCGGUAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 11
            MeanSequenceLength: 11
               DeficitEditData: [1814×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 1814 random sequences, 0 from an alignment, and 1 from 3D structures
Group  60, HL_23010.1  has acceptance rules AlignmentScore >= -27.8097, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.7710
TP   100.00%, TN    95.98%, min    95.98%,   1 3D sequences,     0 alignment sequences, 1814 random sequences,   73 random matches,  8 NTs, cWW-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.98%, Minimum  95.98% using method 6
Number of false positives with core edit > 0 is 73
1 * Deficit + 3 * Core Edit <= 16.9613
Motif index 1


ans = 

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

                       MotifID: 'HL_23115.1'
                     Signature: {'cWW-F-F-F-F-F'}
                         NumNT: 7
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 20
                      OwnScore: [-6.7180 -6.7180]
                   OwnSequence: {'CAGGCGGUUAG'  'CAGGCGGUUAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11]
            MeanSequenceLength: 11
               DeficitEditData: [1040×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 1040 random sequences, 0 from an alignment, and 2 from 3D structures
Group  61, HL_23115.1  has acceptance rules AlignmentScore >= -26.7180, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.7435
TP   100.00%, TN    95.96%, min    95.96%,   2 3D sequences,     0 alignment sequences, 1040 random sequences,   42 random matches,  7 NTs, cWW-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.96%, Minimum  95.96% using method 6
Number of false positives with core edit > 0 is 42
1 * Deficit + 3 * Core Edit <= 19.0255
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_23509.1'
                     Signature: {'cSH-F-F-F-F-F-F-F-F-F'}
                         NumNT: 11
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 36
                      OwnScore: -5.4579
                   OwnSequence: {'GAAUUCAUUUUC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 12
            MeanSequenceLength: 12
               DeficitEditData: [630×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 630 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  20.0797 because the cutoff seemed overly generous
Group  62, HL_23509.1  has acceptance rules AlignmentScore >= -25.4579, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.4579
TP   100.00%, TN    96.35%, min    96.35%,   1 3D sequences,     0 alignment sequences,  630 random sequences,   23 random matches, 11 NTs, cSH-F-F-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.35%, Minimum  96.35% 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: 'HL_24792.1'
                     Signature: {'cWW-cWS-F-F-F'}
                         NumNT: 6
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 22
                      OwnScore: -6.4227
                   OwnSequence: {'GCCCGUUAUC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 10
            MeanSequenceLength: 10
               DeficitEditData: [1042×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 1042 random sequences, 0 from an alignment, and 1 from 3D structures
Group  63, HL_24792.1  has acceptance rules AlignmentScore >= -26.4227, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.1753
TP   100.00%, TN    95.87%, min    95.87%,   1 3D sequences,     0 alignment sequences, 1042 random sequences,   43 random matches,  6 NTs, cWW-cWS-F-F-F
Sensitivity 100.00%, Specificity  95.87%, Minimum  95.87% using method 6
Number of false positives with core edit > 0 is 43
1 * Deficit + 3 * Core Edit <= 17.7526
Motif index 1


ans = 

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

                       MotifID: 'HL_25061.1'
                     Signature: {'cWW-F-F-F-F'}
                         NumNT: 5
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: [-8.7371 -10.8535]
                   OwnSequence: {'UGUGAGAGG'  'CUGUUUUGACG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 11]
            MeanSequenceLength: 10
               DeficitEditData: [6150×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 6150 random sequences, 0 from an alignment, and 2 from 3D structures
Group  64, HL_25061.1  has acceptance rules AlignmentScore >= -28.7371, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  21.8134
TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 6150 random sequences,  246 random matches,  5 NTs, cWW-F-F-F-F
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 246
1 * Deficit + 3 * Core Edit <= 13.0763
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_25847.2'
                     Signature: {'cWW-F-cSH-tHW-F-F-F'}
                         NumNT: 10
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 2
                         NumBR: 1
                  NumInstances: 3
                      Truncate: [0×1 double]
                      NumFixed: 26
                      OwnScore: [-4.3430 -4.8330 -4.3430]
                   OwnSequence: {'GUAACUAUAAC'  'GUAACUAUGAC'  'GUAACUAUAAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11 11]
            MeanSequenceLength: 11
               DeficitEditData: [2143×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 2143 random sequences, 0 from an alignment, and 3 from 3D structures
Decreased cutoff from  20.8240 because the cutoff seemed overly generous
Group  65, HL_25847.2  has acceptance rules AlignmentScore >= -24.3430, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.3430
TP   100.00%, TN    97.06%, min    97.06%,   3 3D sequences,     0 alignment sequences, 2143 random sequences,   63 random matches, 10 NTs, cWW-F-cSH-tHW-F-F-F
Sensitivity 100.00%, Specificity  97.06%, Minimum  97.06% using method 8
Number of false positives with core edit > 0 is 63
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: 'HL_25967.2'
                     Signature: {'cWW-cWW-F-F-F'}
                         NumNT: 7
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 3
                      Truncate: [0×1 double]
                      NumFixed: 16
                      OwnScore: [-4.4355 -4.4355 -9.3439]
                   OwnSequence: {'GUUUAUC'  'GUUUAUC'  'CACCUUUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 7 8]
            MeanSequenceLength: 7.3333
               DeficitEditData: [5228×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 5228 random sequences, 0 from an alignment, and 3 from 3D structures
Group  66, HL_25967.2  has acceptance rules AlignmentScore >= -24.4355, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.7939
TP   100.00%, TN    96.00%, min    96.00%,   3 3D sequences,     0 alignment sequences, 5226 random sequences,  209 random matches,  7 NTs, cWW-cWW-F-F-F
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 209
1 * Deficit + 3 * Core Edit <= 12.3584
Motif index 1
Motif index 2
Motif index 3


ans = 

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

                       MotifID: 'HL_26631.1'
                     Signature: {'cWW-F-F-F'}
                         NumNT: 5
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 2
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 14
                      OwnScore: [-2.5658 -2.5658]
                   OwnSequence: {'CAGUG'  'CAGUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [5 5]
            MeanSequenceLength: 5
               DeficitEditData: [3016×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 3016 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  67, HL_26631.1  has acceptance rules AlignmentScore >= -22.5658, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  12.0658
TP   100.00%, TN    90.40%, min    90.40%,   2 3D sequences,     0 alignment sequences, 3011 random sequences,  289 random matches,  5 NTs, cWW-F-F-F
Sensitivity 100.00%, Specificity  90.40%, Minimum  90.40% using method 11
Number of false positives with core edit > 0 is 289
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: 'HL_26934.1'
                     Signature: {'cWW-F-F-F-F-F-F'}
                         NumNT: 8
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 2
                         NumBR: 1
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 22
                      OwnScore: -3.7607
                   OwnSequence: {'GUGUCUAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 8
            MeanSequenceLength: 8
               DeficitEditData: [5181×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 5181 random sequences, 0 from an alignment, and 1 from 3D structures
Group  68, HL_26934.1  has acceptance rules AlignmentScore >= -23.7607, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  19.8123
TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences, 5181 random sequences,  208 random matches,  8 NTs, cWW-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 208
1 * Deficit + 3 * Core Edit <= 16.0515
Motif index 1


ans = 

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

                       MotifID: 'HL_27483.1'
                     Signature: {'cWW-F'}
                         NumNT: 4
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 2
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 12
                      OwnScore: [-8.1054 -4.1923]
                   OwnSequence: {'GCUUCUGC'  'CGUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 4]
            MeanSequenceLength: 6
               DeficitEditData: [6255×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 6255 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  69, HL_27483.1  has acceptance rules AlignmentScore >= -24.1923, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.6923
TP   100.00%, TN    80.97%, min    80.97%,   2 3D sequences,     0 alignment sequences, 6159 random sequences, 1172 random matches,  4 NTs, cWW-F
Sensitivity 100.00%, Specificity  80.97%, Minimum  80.97% 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


ans = 

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

                       MotifID: 'HL_27670.2'
                     Signature: {'cWW-tWH-F-F'}
                         NumNT: 6
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 13
                      Truncate: [0×1 double]
                      NumFixed: 16
                      OwnScore: [-8.4207 -8.9315 -6.5961 -6.4358 -6.3068 -6.3068 -5.8589 -7.7495 -5.8589 -7.7495 -5.4314 -5.4314 -5.7960]
                   OwnSequence: {1×13 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 9 9 9 9 8 9 8 9 8 8 9]
            MeanSequenceLength: 8.6923
               DeficitEditData: [5543×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

13 sequences from 3D structures
Using 5543 random sequences, 0 from an alignment, and 13 from 3D structures
Group  70, HL_27670.2  has acceptance rules AlignmentScore >= -25.4314, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  18.4849
TP   100.00%, TN    95.99%, min    95.99%,  13 3D sequences,     0 alignment sequences, 5540 random sequences,  222 random matches,  6 NTs, cWW-tWH-F-F
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 <= 13.0534
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: 'HL_28075.1'
                     Signature: {'cWW-F-F-F-F-F'}
                         NumNT: 7
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 4
                      Truncate: [0×1 double]
                      NumFixed: 20
                      OwnScore: [-9.4253 -7.8217 -9.7881 -8.0266]
                   OwnSequence: {'AUGUCGUUU'  'GAUUUUUC'  'CCGAAUAG'  'CUUUUUAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 8 8 8]
            MeanSequenceLength: 8.2500
               DeficitEditData: [7177×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 7177 random sequences, 0 from an alignment, and 4 from 3D structures
Group  71, HL_28075.1  has acceptance rules AlignmentScore >= -27.8217, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.7105
TP   100.00%, TN    96.00%, min    96.00%,   4 3D sequences,     0 alignment sequences, 7176 random sequences,  287 random matches,  7 NTs, cWW-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 287
1 * Deficit + 3 * Core Edit <= 9.8888
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: 'HL_28252.8'
                     Signature: {'cWW-tWH-F-F-F-F-F'}
                         NumNT: 9
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 3
                         NumBR: 1
                  NumInstances: 140
                      Truncate: [0×1 double]
                      NumFixed: 24
                      OwnScore: [-3.0609 -2.6287 -2.7926 -2.7926 -2.7926 -2.6287 -3.0609 -3.0609 -2.7926 -3.0609 -2.7926 -3.0609 -2.3605 … ]
                   OwnSequence: {1×140 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 … ]
            MeanSequenceLength: 9.0500
               DeficitEditData: [1990×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

140 sequences from 3D structures
Using 1990 random sequences, 0 from an alignment, and 140 from 3D structures
Group  72, HL_28252.8  has acceptance rules AlignmentScore >= -22.3605, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.7241
TP    97.86%, TN    96.02%, min    96.02%, 140 3D sequences,     0 alignment sequences, 1984 random sequences,   79 random matches,  9 NTs, cWW-tWH-F-F-F-F-F
Sensitivity  97.86%, Specificity  96.02%, Minimum  96.02% using method 6
Number of false positives with core edit > 0 is 79
1 * Deficit + 3 * Core Edit <= 15.3636
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


ans = 

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

                       MotifID: 'HL_28791.1'
                     Signature: {'cWW-F-F-F-F'}
                         NumNT: 6
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 16
                      OwnScore: -3.7921
                   OwnSequence: {'CGCGUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 6
            MeanSequenceLength: 6
               DeficitEditData: [3987×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 3987 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  73, HL_28791.1  has acceptance rules AlignmentScore >= -23.7921, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.2921
TP   100.00%, TN    95.03%, min    95.03%,   1 3D sequences,     0 alignment sequences, 3982 random sequences,  198 random matches,  6 NTs, cWW-F-F-F-F
Sensitivity 100.00%, Specificity  95.03%, Minimum  95.03% using method 11
Number of false positives with core edit > 0 is 198
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: 'HL_29129.3'
                     Signature: {'cWW-tWH-F-F-F-F'}
                         NumNT: 8
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 3
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: [-6.8801 -6.8801 -8.4073]
                   OwnSequence: {'UUUGGGGAAAG'  'UUUGGGGAAAG'  'GUUGGGGAUC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11 10]
            MeanSequenceLength: 10.6667
               DeficitEditData: [2549×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 2549 random sequences, 0 from an alignment, and 3 from 3D structures
Group  74, HL_29129.3  has acceptance rules AlignmentScore >= -26.8801, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  23.8858
TP   100.00%, TN    95.96%, min    95.96%,   3 3D sequences,     0 alignment sequences, 2549 random sequences,  103 random matches,  8 NTs, cWW-tWH-F-F-F-F
Sensitivity 100.00%, Specificity  95.96%, Minimum  95.96% using method 6
Number of false positives with core edit > 0 is 103
1 * Deficit + 3 * Core Edit <= 17.0057
Motif index 1
Motif index 2
Motif index 3


ans = 

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

                       MotifID: 'HL_29762.1'
                     Signature: {'cWW-F-F-F-F-F'}
                         NumNT: 7
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 20
                      OwnScore: -9.0440
                   OwnSequence: {'UUGAUAUGAUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 11
            MeanSequenceLength: 11
               DeficitEditData: [3401×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 3401 random sequences, 0 from an alignment, and 1 from 3D structures
Group  75, HL_29762.1  has acceptance rules AlignmentScore >= -29.0440, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.4066
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 3401 random sequences,  136 random matches,  7 NTs, cWW-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 136
1 * Deficit + 3 * Core Edit <= 17.3626
Motif index 1


ans = 

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

                       MotifID: 'HL_29958.1'
                     Signature: {'cWW-F-F-F-F-F-F-F-F'}
                         NumNT: 10
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 26
                      OwnScore: -9.9378
                   OwnSequence: {'AGGUGGGGUUUAU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 13
            MeanSequenceLength: 13
               DeficitEditData: [219×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 219 random sequences, 0 from an alignment, and 1 from 3D structures
Group  76, HL_29958.1  has acceptance rules AlignmentScore >= -29.9378, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.7543
TP   100.00%, TN    95.89%, min    95.89%,   1 3D sequences,     0 alignment sequences,  219 random sequences,    9 random matches, 10 NTs, cWW-F-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.89%, Minimum  95.89% using method 6
Number of false positives with core edit > 0 is 9
1 * Deficit + 3 * Core Edit <= 16.8165
Motif index 1


ans = 

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

                       MotifID: 'HL_29966.1'
                     Signature: {'cWW-F-F-F'}
                         NumNT: 5
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 14
                      OwnScore: -4.4128
                   OwnSequence: {'AAAUUU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 6
            MeanSequenceLength: 6
               DeficitEditData: [4707×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 4707 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  77, HL_29966.1  has acceptance rules AlignmentScore >= -24.4128, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.9128
TP   100.00%, TN    89.96%, min    89.96%,   1 3D sequences,     0 alignment sequences, 4700 random sequences,  472 random matches,  5 NTs, cWW-F-F-F
Sensitivity 100.00%, Specificity  89.96%, Minimum  89.96% using method 11
Number of false positives with core edit > 0 is 472
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: 'HL_30068.2'
                     Signature: {'cWW-F-F-F-F'}
                         NumNT: 6
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 15
                      Truncate: [0×1 double]
                      NumFixed: 14
                      OwnScore: [-6.0518 -6.0518 -6.3560 -6.3560 -6.3560 -6.3560 -6.3560 -6.2638 -6.2638 -6.2638 -6.2588 -6.2588 -6.2638 … ]
                   OwnSequence: {1×15 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8 8 8 8 8 8 7 7 7 7 7 7 7 7]
            MeanSequenceLength: 7.4667
               DeficitEditData: [6688×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

15 sequences from 3D structures
Using 6688 random sequences, 0 from an alignment, and 15 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  78, HL_30068.2  has acceptance rules AlignmentScore >= -26.0518, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.5518
TP   100.00%, TN    95.53%, min    95.53%,  15 3D sequences,     0 alignment sequences, 6686 random sequences,  299 random matches,  6 NTs, cWW-F-F-F-F
Sensitivity 100.00%, Specificity  95.53%, Minimum  95.53% using method 11
Number of false positives with core edit > 0 is 299
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


ans = 

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

                       MotifID: 'HL_30680.3'
                     Signature: {'cWW-F-F-F-F-F'}
                         NumNT: 7
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 15
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: [-6.4673 -6.4673 -10.0395 -6.4673 -6.4673 -8.0106 -11.9052 -9.0552 -7.6802 -9.0552 -7.3437 -7.6802 … ]
                   OwnSequence: {1×15 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 7 7 7 7 7 7 8 8 8 8 8 8 9 9]
            MeanSequenceLength: 7.6667
               DeficitEditData: [5823×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

15 sequences from 3D structures
Using 5823 random sequences, 0 from an alignment, and 15 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  79, HL_30680.3  has acceptance rules AlignmentScore >= -26.4673, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.9673
TP   100.00%, TN    95.43%, min    95.43%,  15 3D sequences,     0 alignment sequences, 5815 random sequences,  266 random matches,  7 NTs, cWW-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.43%, Minimum  95.43% using method 11
Number of false positives with core edit > 0 is 266
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


ans = 

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

                       MotifID: 'HL_31581.6'
                     Signature: {'cWW-cHS-F-F-F-cWW-F-F-F'}
                         NumNT: 11
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 3
                      Truncate: [0×1 double]
                      NumFixed: 28
                      OwnScore: [-7.1505 -7.1505 -9.2504]
                   OwnSequence: {'CAUUGCACUCCG'  'CAUUGCACUCCG'  'UAUUGCAGUACCG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [12 12 13]
            MeanSequenceLength: 12.3333
               DeficitEditData: [611×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 611 random sequences, 0 from an alignment, and 3 from 3D structures
Decreased cutoff from  21.5966 because the cutoff seemed overly generous
Group  80, HL_31581.6  has acceptance rules AlignmentScore >= -27.1505, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  27.1505
TP   100.00%, TN    97.55%, min    97.55%,   3 3D sequences,     0 alignment sequences,  611 random sequences,   15 random matches, 11 NTs, cWW-cHS-F-F-F-cWW-F-F-F
Sensitivity 100.00%, Specificity  97.55%, Minimum  97.55% using method 8
Number of false positives with core edit > 0 is 15
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: 'HL_31585.4'
                     Signature: {'cWW-F-F-F-F-F'}
                         NumNT: 7
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 20
                      Truncate: [0×1 double]
                      NumFixed: 20
                      OwnScore: [-6.4455 -6.4455 -6.4455 -6.4455 -8.2398 -6.4455 -7.0815 -8.2398 -11.5371 -7.9450 -14.7779 -9.1882 … ]
                   OwnSequence: {1×20 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8 8 8 8 8 8 8 7 7 8 8 8 8 8 8 8 8 8 8]
            MeanSequenceLength: 7.9000
               DeficitEditData: [6188×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

20 sequences from 3D structures
Using 6188 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  81, HL_31585.4  has acceptance rules AlignmentScore >= -26.4455, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.9455
TP   100.00%, TN    93.04%, min    93.04%,  20 3D sequences,     0 alignment sequences, 6175 random sequences,  430 random matches,  7 NTs, cWW-F-F-F-F-F
Sensitivity 100.00%, Specificity  93.04%, Minimum  93.04% using method 11
Number of false positives with core edit > 0 is 430
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: 'HL_32346.4'
                     Signature: {'cWW-F'}
                         NumNT: 3
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 2
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 9
                      Truncate: [0×1 double]
                      NumFixed: 10
                      OwnScore: [-8.0390 -5.6093 -5.3317 -4.0119 -4.9783 -4.8208 -4.2348 -4.4110 -4.8003]
                   OwnSequence: {'CGGAUG'  'CAAUG'  'CUUCG'  'CGUG'  'UUCA'  'CAUUG'  'GGUC'  'UUUUA'  'CUCG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 5 5 4 4 5 4 5 4]
            MeanSequenceLength: 4.6667
               DeficitEditData: [4897×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

9 sequences from 3D structures
Using 4897 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  82, HL_32346.4  has acceptance rules AlignmentScore >= -24.0119, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.5119
TP   100.00%, TN    62.41%, min    62.41%,   9 3D sequences,     0 alignment sequences, 4634 random sequences, 1742 random matches,  3 NTs, cWW-F
Sensitivity 100.00%, Specificity  62.41%, Minimum  62.41% using method 11
Number of false positives with core edit > 0 is 1742
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: 'HL_32392.1'
                     Signature: {'cWW-F-F'}
                         NumNT: 4
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 14
                      OwnScore: [-3.6707 -4.3639]
                   OwnSequence: {'UUUGA'  'UUUCGA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [5 6]
            MeanSequenceLength: 5.5000
               DeficitEditData: [5382×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 5382 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  83, HL_32392.1  has acceptance rules AlignmentScore >= -23.6707, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.1707
TP   100.00%, TN    84.55%, min    84.55%,   2 3D sequences,     0 alignment sequences, 5352 random sequences,  827 random matches,  4 NTs, cWW-F-F
Sensitivity 100.00%, Specificity  84.55%, Minimum  84.55% using method 11
Number of false positives with core edit > 0 is 827
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: 'HL_32735.2'
                     Signature: {'cWW-tSH-F-F-F-F-F'}
                         NumNT: 9
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 4
                         NumBR: 2
                  NumInstances: 7
                      Truncate: [0×1 double]
                      NumFixed: 20
                      OwnScore: [-3.6330 -3.6630 -4.4214 -5.1272 -4.3087 -3.6630 -6.4343]
                   OwnSequence: {'AGUUCAUAU'  'CGUUCAUAG'  'AGUUCACAU'  'CGUCCACAG'  'AGUCCAUAU'  'CGUUCAUAG'  'AGCACAUAU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 9 9 9 9 9]
            MeanSequenceLength: 9
               DeficitEditData: [1569×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

7 sequences from 3D structures
Using 1569 random sequences, 0 from an alignment, and 7 from 3D structures
Group  84, HL_32735.2  has acceptance rules AlignmentScore >= -23.6330, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  20.5201
TP   100.00%, TN    95.98%, min    95.98%,   7 3D sequences,     0 alignment sequences, 1569 random sequences,   63 random matches,  9 NTs, cWW-tSH-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.98%, Minimum  95.98% using method 6
Number of false positives with core edit > 0 is 63
1 * Deficit + 3 * Core Edit <= 16.8871
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: 'HL_33074.4'
                     Signature: {'cWW-F-F-F-F-F-F-F-F'}
                         NumNT: 10
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 22
                      Truncate: [0×1 double]
                      NumFixed: 28
                      OwnScore: [-1.8806 -1.8806 -1.8806 -1.8806 -1.8806 -1.8806 -6.0889 -1.8806 -1.8806 -6.0889 -1.8806 -1.8806 -1.8806 … ]
                   OwnSequence: {1×22 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12]
            MeanSequenceLength: 12
               DeficitEditData: [59×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

22 sequences from 3D structures
Using 59 random sequences, 0 from an alignment, and 22 from 3D structures
Decreased cutoff from  21.5989 because the cutoff seemed overly generous
Group  85, HL_33074.4  has acceptance rules AlignmentScore >= -21.8806, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  21.8806
TP   100.00%, TN    98.31%, min    98.31%,  22 3D sequences,     0 alignment sequences,   59 random sequences,    1 random matches, 10 NTs, cWW-F-F-F-F-F-F-F-F
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 <= 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
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: 'HL_33983.1'
                     Signature: {'cWW-F-F-F-F-F'}
                         NumNT: 7
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 20
                      OwnScore: -6.5674
                   OwnSequence: {'CCUGAUAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 9
            MeanSequenceLength: 9
               DeficitEditData: [5528×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 5528 random sequences, 0 from an alignment, and 1 from 3D structures
Group  86, HL_33983.1  has acceptance rules AlignmentScore >= -26.5674, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  20.4684
TP   100.00%, TN    95.97%, min    95.97%,   1 3D sequences,     0 alignment sequences, 5528 random sequences,  223 random matches,  7 NTs, cWW-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.97%, Minimum  95.97% using method 6
Number of false positives with core edit > 0 is 223
1 * Deficit + 3 * Core Edit <= 13.9010
Motif index 1


ans = 

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

                       MotifID: 'HL_34617.5'
                     Signature: {'cWW-tSW-F'}
                         NumNT: 5
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 57
                      Truncate: [0×1 double]
                      NumFixed: 12
                      OwnScore: [-1.9414 -2.8691 -1.9414 -1.9414 -2.8691 -1.9414 -2.9635 -1.9414 -1.9414 -2.8691 -1.9414 -1.9414 -1.9414 … ]
                   OwnSequence: {1×57 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: 6.0175
               DeficitEditData: [4523×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

57 sequences from 3D structures
Using 4523 random sequences, 0 from an alignment, and 57 from 3D structures
Group  87, HL_34617.5  has acceptance rules AlignmentScore >= -21.9414, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  11.9194
TP    98.25%, TN    96.01%, min    96.01%,  57 3D sequences,     0 alignment sequences, 4484 random sequences,  179 random matches,  5 NTs, cWW-tSW-F
Sensitivity  98.25%, Specificity  96.01%, Minimum  96.01% using method 6
Number of false positives with core edit > 0 is 179
1 * Deficit + 3 * Core Edit <= 9.9780
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


ans = 

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

                       MotifID: 'HL_34964.1'
                     Signature: {'cWW-F-F-F-F-F'}
                         NumNT: 9
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: [-10.9853 -9.5519]
                   OwnSequence: {'AGAGGGGCUUU'  'GUUUUGUAAUC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11]
            MeanSequenceLength: 11
               DeficitEditData: [2682×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 2682 random sequences, 0 from an alignment, and 2 from 3D structures
Group  88, HL_34964.1  has acceptance rules AlignmentScore >= -29.5519, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.4716
TP   100.00%, TN    96.01%, min    96.01%,   2 3D sequences,     0 alignment sequences, 2682 random sequences,  107 random matches,  9 NTs, cWW-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.01%, Minimum  96.01% using method 6
Number of false positives with core edit > 0 is 107
1 * Deficit + 3 * Core Edit <= 15.9197
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_35354.1'
                     Signature: {'cWW-cWH-cHW-F-cWH-cHW-F-F-tHH-cWH-tWW-cWH-F-tWW-cWH-F-cWH'}
                         NumNT: 21
                  NumBasepairs: 14
                    Structured: 1
                     NumStacks: 20
                        NumBPh: 1
                         NumBR: 2
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 40
                      OwnScore: -10.3000
                   OwnSequence: {'AGGAAGGAUUGGUAUGUGGUAUAU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 24
            MeanSequenceLength: 24
               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  89, HL_35354.1  has acceptance rules AlignmentScore >= -30.3000, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  35.3000
TP   100.00%, TN      NaN%, min   100.00%,   1 3D sequences,     0 alignment sequences,    0 random sequences,    0 random matches, 21 NTs, cWW-cWH-cHW-F-cWH-cHW-F-F-tHH-cWH-tWW-cWH-F-tWW-cWH-F-cWH
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: 'HL_35677.3'
                     Signature: {'cWW-F-F-F-F-F-F-F'}
                         NumNT: 9
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 7
                      Truncate: [0×1 double]
                      NumFixed: 26
                      OwnScore: [-7.3767 -7.3767 -7.3767 -11.6458 -10.0137 -10.0137 -12.6952]
                   OwnSequence: {'UGAUUUGCUA'  'UGAUUUGCUA'  'UGAUUUGCUA'  'UGCUAAUCUG'  'CGGCUUCCUG'  'CGGCUUCCUG'  'CUUCCUGCG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10 10 10 10 10 9]
            MeanSequenceLength: 9.8571
               DeficitEditData: [4670×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

7 sequences from 3D structures
Using 4670 random sequences, 0 from an alignment, and 7 from 3D structures
Group  90, HL_35677.3  has acceptance rules AlignmentScore >= -27.3767, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  22.7726
TP   100.00%, TN    95.99%, min    95.99%,   7 3D sequences,     0 alignment sequences, 4669 random sequences,  187 random matches,  9 NTs, cWW-F-F-F-F-F-F-F
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 <= 15.3959
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: 'HL_35941.1'
                     Signature: {'cWW-F'}
                         NumNT: 3
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 1
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 10
                      OwnScore: -3.7846
                   OwnSequence: {'CUCGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 5
            MeanSequenceLength: 5
               DeficitEditData: [5132×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 5132 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  91, HL_35941.1  has acceptance rules AlignmentScore >= -23.7846, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.2846
TP   100.00%, TN    76.86%, min    76.86%,   1 3D sequences,     0 alignment sequences, 5112 random sequences, 1183 random matches,  3 NTs, cWW-F
Sensitivity 100.00%, Specificity  76.86%, Minimum  76.86% using method 11
Number of false positives with core edit > 0 is 1183
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: 'HL_36335.1'
                     Signature: {'cWW-F-F-cSS-cSS-F'}
                         NumNT: 9
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 22
                      OwnScore: [-7.9142 -7.9142]
                   OwnSequence: {'CAAGAAAGAG'  'CAAGAAAGAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10]
            MeanSequenceLength: 10
               DeficitEditData: [3999×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 3999 random sequences, 0 from an alignment, and 2 from 3D structures
Group  92, HL_36335.1  has acceptance rules AlignmentScore >= -27.9142, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  22.0463
TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 3997 random sequences,  160 random matches,  9 NTs, cWW-F-F-cSS-cSS-F
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 160
1 * Deficit + 3 * Core Edit <= 14.1322
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_36684.4'
                     Signature: {'cWW-F-F-F-F-F-F-F-F-F'}
                         NumNT: 11
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 7
                      Truncate: [0×1 double]
                      NumFixed: 26
                      OwnScore: [-10.4890 -7.8135 -8.4013 -11.3100 -10.5479 -8.7351 -9.8337]
                   OwnSequence: {'GACUUUUAAUC'  'GCUUGAGAACC'  'GAUUGUGAUUC'  'GGUUCGGCGUC'  'GGCUACGAACC'  'CCUUGGUAAGG'  'CCUUGAGGUGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11 11 11 11 11 11]
            MeanSequenceLength: 11
               DeficitEditData: [2187×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

7 sequences from 3D structures
Using 2187 random sequences, 0 from an alignment, and 7 from 3D structures
Group  93, HL_36684.4  has acceptance rules AlignmentScore >= -27.8135, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.9309
TP   100.00%, TN    96.02%, min    96.02%,   7 3D sequences,     0 alignment sequences, 2187 random sequences,   87 random matches, 11 NTs, cWW-F-F-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.02%, Minimum  96.02% using method 6
Number of false positives with core edit > 0 is 87
1 * Deficit + 3 * Core Edit <= 17.1174
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: 'HL_37344.1'
                     Signature: {'cWW-F-F'}
                         NumNT: 6
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 14
                      OwnScore: [-8.1047 -6.4857]
                   OwnSequence: {'CCAUUCGG'  'CCUUGAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 7]
            MeanSequenceLength: 7.5000
               DeficitEditData: [6952×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 6952 random sequences, 0 from an alignment, and 2 from 3D structures
Group  94, HL_37344.1  has acceptance rules AlignmentScore >= -26.4857, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.0921
TP   100.00%, TN    95.99%, min    95.99%,   2 3D sequences,     0 alignment sequences, 6952 random sequences,  279 random matches,  6 NTs, cWW-F-F
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 279
1 * Deficit + 3 * Core Edit <= 10.6064
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_37369.2'
                     Signature: {'cWW-tSH-F-F-F'}
                         NumNT: 7
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 3
                         NumBR: 0
                  NumInstances: 9
                      Truncate: [0×1 double]
                      NumFixed: 16
                      OwnScore: [-3.3463 -3.3463 -3.3463 -3.3463 -3.3463 -3.3463 -4.8816 -7.5497 -7.5497]
                   OwnSequence: {'CGGCGAG'  'CGGCGAG'  'CGGCGAG'  'CGGCGAG'  'CGGCGAG'  'CGGCGAG'  'CCGCGAG'  'UUUCAAG'  'UUUCAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 7 7 7 7 7 7 7 7]
            MeanSequenceLength: 7
               DeficitEditData: [2888×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

9 sequences from 3D structures
Using 2888 random sequences, 0 from an alignment, and 9 from 3D structures
Group  95, HL_37369.2  has acceptance rules AlignmentScore >= -23.3463, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.5853
TP   100.00%, TN    95.98%, min    95.98%,   9 3D sequences,     0 alignment sequences, 2883 random sequences,  116 random matches,  7 NTs, cWW-tSH-F-F-F
Sensitivity 100.00%, Specificity  95.98%, Minimum  95.98% using method 6
Number of false positives with core edit > 0 is 116
1 * Deficit + 3 * Core Edit <= 13.2390
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: 'HL_37824.7'
                     Signature: {'cWW-F-F-F-F'}
                         NumNT: 6
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 349
                      Truncate: [0×1 double]
                      NumFixed: 16
                      OwnScore: [-1.7593 -1.7593 -1.7593 -1.7593 -1.7593 -1.7593 -1.7593 -1.7593 -1.7593 -3.2985 -1.7593 -1.7593 -2.5448 … ]
                   OwnSequence: {1×349 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: 6.1089
               DeficitEditData: [4958×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

349 sequences from 3D structures
Using 4958 random sequences, 0 from an alignment, and 349 from 3D structures
Group  96, HL_37824.7  has acceptance rules AlignmentScore >= -21.7593, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  11.3528
TP    97.42%, TN    95.93%, min    95.93%, 349 3D sequences,     0 alignment sequences, 4674 random sequences,  190 random matches,  6 NTs, cWW-F-F-F-F
Sensitivity  97.42%, Specificity  95.93%, Minimum  95.93% using method 6
Number of false positives with core edit > 0 is 190
1 * Deficit + 3 * Core Edit <= 9.5935
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
Motif index 180
Motif index 181
Motif index 182
Motif index 183
Motif index 184
Motif index 185
Motif index 186
Motif index 187
Motif index 188
Motif index 189
Motif index 190
Motif index 191
Motif index 192
Motif index 193
Motif index 194
Motif index 195
Motif index 196
Motif index 197
Motif index 198
Motif index 199
Motif index 200
Motif index 201
Motif index 202
Motif index 203
Motif index 204
Motif index 205
Motif index 206
Motif index 207
Motif index 208
Motif index 209
Motif index 210
Motif index 211
Motif index 212
Motif index 213
Motif index 214
Motif index 215
Motif index 216
Motif index 217
Motif index 218
Motif index 219
Motif index 220
Motif index 221
Motif index 222
Motif index 223
Motif index 224
Motif index 225
Motif index 226
Motif index 227
Motif index 228
Motif index 229
Motif index 230
Motif index 231
Motif index 232
Motif index 233
Motif index 234
Motif index 235
Motif index 236
Motif index 237
Motif index 238
Motif index 239
Motif index 240
Motif index 241
Motif index 242
Motif index 243
Motif index 244
Motif index 245
Motif index 246
Motif index 247
Motif index 248
Motif index 249
Motif index 250
Motif index 251
Motif index 252
Motif index 253
Motif index 254
Motif index 255
Motif index 256
Motif index 257
Motif index 258
Motif index 259
Motif index 260
Motif index 261
Motif index 262
Motif index 263
Motif index 264
Motif index 265
Motif index 266
Motif index 267
Motif index 268
Motif index 269
Motif index 270
Motif index 271
Motif index 272
Motif index 273
Motif index 274
Motif index 275
Motif index 276
Motif index 277
Motif index 278
Motif index 279
Motif index 280
Motif index 281
Motif index 282
Motif index 283
Motif index 284
Motif index 285
Motif index 286
Motif index 287
Motif index 288
Motif index 289
Motif index 290
Motif index 291
Motif index 292
Motif index 293
Motif index 294
Motif index 295
Motif index 296
Motif index 297
Motif index 298
Motif index 299
Motif index 300
Motif index 301
Motif index 302
Motif index 303
Motif index 304
Motif index 305
Motif index 306
Motif index 307
Motif index 308
Motif index 309
Motif index 310
Motif index 311
Motif index 312
Motif index 313
Motif index 314
Motif index 315
Motif index 316
Motif index 317
Motif index 318
Motif index 319
Motif index 320
Motif index 321
Motif index 322
Motif index 323
Motif index 324
Motif index 325
Motif index 326
Motif index 327
Motif index 328
Motif index 329
Motif index 330
Motif index 331
Motif index 332
Motif index 333
Motif index 334
Motif index 335
Motif index 336
Motif index 337
Motif index 338
Motif index 339
Motif index 340
Motif index 341
Motif index 342
Motif index 343
Motif index 344
Motif index 345
Motif index 346
Motif index 347
Motif index 348
Motif index 349


ans = 

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

                       MotifID: 'HL_38046.1'
                     Signature: {'cWW-F-F-F-F-F-F'}
                         NumNT: 8
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 22
                      OwnScore: -6.5024
                   OwnSequence: {'AAAAUCACU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 9
            MeanSequenceLength: 9
               DeficitEditData: [4599×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 4599 random sequences, 0 from an alignment, and 1 from 3D structures
Group  97, HL_38046.1  has acceptance rules AlignmentScore >= -26.5024, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  21.1009
TP   100.00%, TN    95.98%, min    95.98%,   1 3D sequences,     0 alignment sequences, 4599 random sequences,  185 random matches,  8 NTs, cWW-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.98%, Minimum  95.98% using method 6
Number of false positives with core edit > 0 is 185
1 * Deficit + 3 * Core Edit <= 14.5984
Motif index 1


ans = 

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

                       MotifID: 'HL_38168.1'
                     Signature: {'cWW-F'}
                         NumNT: 3
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 1
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 10
                      OwnScore: [-4.9890 -7.9710]
                   OwnSequence: {'CAAAG'  'CUGUUCG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [5 7]
            MeanSequenceLength: 6
               DeficitEditData: [6589×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 6589 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  98, HL_38168.1  has acceptance rules AlignmentScore >= -24.9890, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  14.4890
TP   100.00%, TN    81.17%, min    81.17%,   2 3D sequences,     0 alignment sequences, 6528 random sequences, 1229 random matches,  3 NTs, cWW-F
Sensitivity 100.00%, Specificity  81.17%, Minimum  81.17% using method 11
Number of false positives with core edit > 0 is 1229
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: 'HL_38649.1'
                     Signature: {'cWW-tSH-F-F-F-F-F-F'}
                         NumNT: 10
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 5
                      Truncate: [0×1 double]
                      NumFixed: 22
                      OwnScore: [-10.1131 -10.1131 -14.1174 -15.2238 -13.9722]
                   OwnSequence: {'GGAACACUAUAC'  'GGAACACUAUAC'  'CGGCGCAUGCAG'  'GUGCAGCCCGUC'  'CUGACCGAUAUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [12 12 12 12 12]
            MeanSequenceLength: 12
               DeficitEditData: [2399×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

5 sequences from 3D structures
Using 2399 random sequences, 0 from an alignment, and 5 from 3D structures
Group  99, HL_38649.1  has acceptance rules AlignmentScore >= -30.1131, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.8210
TP   100.00%, TN    96.00%, min    96.00%,   5 3D sequences,     0 alignment sequences, 2399 random sequences,   96 random matches, 10 NTs, cWW-tSH-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 96
1 * Deficit + 3 * Core Edit <= 16.7080
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: 'HL_38808.1'
                     Signature: {'cWW-cWW'}
                         NumNT: 4
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 2
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 4
                      Truncate: [0×1 double]
                      NumFixed: 12
                      OwnScore: [-8.9167 -8.9167 -11.5827 -12.5733]
                   OwnSequence: {'AUUCCCAUU'  'AUUCCCAUU'  'ACUGCAGAU'  'CUAAUUAGUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 9 10]
            MeanSequenceLength: 9.2500
               DeficitEditData: [6280×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 6280 random sequences, 0 from an alignment, and 4 from 3D structures
Group 100, HL_38808.1  has acceptance rules AlignmentScore >= -28.9167, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  21.8234
TP   100.00%, TN    95.97%, min    95.97%,   4 3D sequences,     0 alignment sequences, 6280 random sequences,  253 random matches,  4 NTs, cWW-cWW
Sensitivity 100.00%, Specificity  95.97%, Minimum  95.97% using method 6
Number of false positives with core edit > 0 is 253
1 * Deficit + 3 * Core Edit <= 12.9067
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: 'HL_38901.2'
                     Signature: {'cWW-F-cSH'}
                         NumNT: 5
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 2
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 7
                      Truncate: [0×1 double]
                      NumFixed: 14
                      OwnScore: [-5.0358 -4.9741 -4.8846 -4.8846 -6.6480 -6.8509 -7.3958]
                   OwnSequence: {'UUGGUA'  'CUGGUG'  'GUGGUC'  'GUGGUC'  'GAGUC'  'CAUUUG'  'GGAAAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 6 6 5 6 6]
            MeanSequenceLength: 5.8571
               DeficitEditData: [5212×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

7 sequences from 3D structures
Using 5212 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 101, HL_38901.2  has acceptance rules AlignmentScore >= -24.8846, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  14.3846
TP   100.00%, TN    76.36%, min    76.36%,   7 3D sequences,     0 alignment sequences, 5160 random sequences, 1220 random matches,  5 NTs, cWW-F-cSH
Sensitivity 100.00%, Specificity  76.36%, Minimum  76.36% using method 11
Number of false positives with core edit > 0 is 1220
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: 'HL_39243.1'
                     Signature: {'cWW-F-F-F-F'}
                         NumNT: 6
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 16
                      OwnScore: [-8.9039 -7.0068]
                   OwnSequence: {'GUUCGAUCC'  'GAAAAUC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 7]
            MeanSequenceLength: 8
               DeficitEditData: [5921×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 5921 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 102, HL_39243.1  has acceptance rules AlignmentScore >= -27.0068, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.5068
TP   100.00%, TN    94.02%, min    94.02%,   2 3D sequences,     0 alignment sequences, 5919 random sequences,  354 random matches,  6 NTs, cWW-F-F-F-F
Sensitivity 100.00%, Specificity  94.02%, Minimum  94.02% using method 11
Number of false positives with core edit > 0 is 354
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: 'HL_40252.4'
                     Signature: {'cWW-tSH-cWS-F'}
                         NumNT: 7
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 5
                      Truncate: [0×1 double]
                      NumFixed: 14
                      OwnScore: [-10.2529 -12.1995 -13.4101 -12.1995 -10.2529]
                   OwnSequence: {'CAAGCGGUAAG'  'CGAGCGGUUGAAG'  'CCAAUGGUCACG'  'CGAGUGGCUGAAG'  'CAAGCGGUAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 13 12 13 11]
            MeanSequenceLength: 12
               DeficitEditData: [2568×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

5 sequences from 3D structures
Using 2568 random sequences, 0 from an alignment, and 5 from 3D structures
Group 103, HL_40252.4  has acceptance rules AlignmentScore >= -30.2529, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.6185
TP   100.00%, TN    95.99%, min    95.99%,   5 3D sequences,     0 alignment sequences, 2568 random sequences,  103 random matches,  7 NTs, cWW-tSH-cWS-F
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 103
1 * Deficit + 3 * Core Edit <= 16.3656
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: 'HL_41464.2'
                     Signature: {'cWW-F-F-F-F-F'}
                         NumNT: 7
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 4
                      Truncate: [0×1 double]
                      NumFixed: 20
                      OwnScore: [-8.0258 -8.0258 -13.1319 -12.9710]
                   OwnSequence: {'GUGUAAAAC'  'GUGUAAAAC'  'CUGUUCGCAG'  'GGUGAAUGAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 10 10]
            MeanSequenceLength: 9.5000
               DeficitEditData: [7927×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 7927 random sequences, 0 from an alignment, and 4 from 3D structures
Group 104, HL_41464.2  has acceptance rules AlignmentScore >= -28.0258, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  18.9136
TP   100.00%, TN    95.99%, min    95.99%,   4 3D sequences,     0 alignment sequences, 7926 random sequences,  318 random matches,  7 NTs, cWW-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 318
1 * Deficit + 3 * Core Edit <= 10.8878
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: 'HL_41543.1'
                     Signature: {'cWW-F-F-F-F-F-F-F-F'}
                         NumNT: 10
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 26
                      OwnScore: [-9.0166 -8.8746]
                   OwnSequence: {'GUGCAGCCCGUC'  'GUUUGCGGGAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [12 11]
            MeanSequenceLength: 11.5000
               DeficitEditData: [2002×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 2002 random sequences, 0 from an alignment, and 2 from 3D structures
Group 105, HL_41543.1  has acceptance rules AlignmentScore >= -28.8746, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.8775
TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 2002 random sequences,   80 random matches, 10 NTs, cWW-F-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 80
1 * Deficit + 3 * Core Edit <= 18.0029
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_41902.1'
                     Signature: {'cWW-cWW-cWH-F-F-F-F-F'}
                         NumNT: 11
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 30
                      OwnScore: [-6.6206 -6.6206]
                   OwnSequence: {'UAGGGAACGGGA'  'UAGGGAACGGGA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [12 12]
            MeanSequenceLength: 12
               DeficitEditData: [606×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 606 random sequences, 0 from an alignment, and 2 from 3D structures
Decreased cutoff from  20.9937 because the cutoff seemed overly generous
Group 106, HL_41902.1  has acceptance rules AlignmentScore >= -26.6206, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.6206
TP   100.00%, TN    97.36%, min    97.36%,   2 3D sequences,     0 alignment sequences,  606 random sequences,   16 random matches, 11 NTs, cWW-cWW-cWH-F-F-F-F-F
Sensitivity 100.00%, Specificity  97.36%, Minimum  97.36% using method 8
Number of false positives with core edit > 0 is 16
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: 'HL_42046.2'
                     Signature: {'cWW-tSS-F-F-F'}
                         NumNT: 7
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 5
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: [-4.6378 -4.6378 -4.6378 -4.6378 -6.2105]
                   OwnSequence: {'CGUUCUAG'  'CGUUCUAG'  'CGUUUUAG'  'CGUUUUAG'  'CGUUGAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8 8 8 7]
            MeanSequenceLength: 7.8000
               DeficitEditData: [5401×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

5 sequences from 3D structures
Using 5401 random sequences, 0 from an alignment, and 5 from 3D structures
Group 107, HL_42046.2  has acceptance rules AlignmentScore >= -24.6378, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.7544
TP   100.00%, TN    95.96%, min    95.96%,   5 3D sequences,     0 alignment sequences, 5398 random sequences,  218 random matches,  7 NTs, cWW-tSS-F-F-F
Sensitivity 100.00%, Specificity  95.96%, Minimum  95.96% using method 6
Number of false positives with core edit > 0 is 218
1 * Deficit + 3 * Core Edit <= 12.1166
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: 'HL_42998.2'
                     Signature: {'cWW-F-F-F-F-F-F'}
                         NumNT: 8
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 2
                         NumBR: 0
                  NumInstances: 7
                      Truncate: [0×1 double]
                      NumFixed: 20
                      OwnScore: [-2.9827 -4.4491 -2.9827 -2.7314 -2.7314 -4.4153 -4.4153]
                   OwnSequence: {'GAAACAAC'  'GAAACAGC'  'GAAACAAC'  'GGAACAAC'  'GGAACAAC'  'GGAUGAAC'  'GGAUGAAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8 8 8 8 8 8]
            MeanSequenceLength: 8
               DeficitEditData: [2324×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

7 sequences from 3D structures
Using 2324 random sequences, 0 from an alignment, and 7 from 3D structures
Group 108, HL_42998.2  has acceptance rules AlignmentScore >= -22.7314, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.1913
TP   100.00%, TN    95.95%, min    95.95%,   7 3D sequences,     0 alignment sequences, 2321 random sequences,   94 random matches,  8 NTs, cWW-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.95%, Minimum  95.95% using method 6
Number of false positives with core edit > 0 is 94
1 * Deficit + 3 * Core Edit <= 12.4599
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: 'HL_43517.1'
                     Signature: {'cWW-F-F-F'}
                         NumNT: 5
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 16
                      OwnScore: [-6.0386 -4.6523]
                   OwnSequence: {'GUUUAUC'  'CUUCG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 5]
            MeanSequenceLength: 6
               DeficitEditData: [6154×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 6154 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 109, HL_43517.1  has acceptance rules AlignmentScore >= -24.6523, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  14.1523
TP   100.00%, TN    89.99%, min    89.99%,   2 3D sequences,     0 alignment sequences, 6135 random sequences,  614 random matches,  5 NTs, cWW-F-F-F
Sensitivity 100.00%, Specificity  89.99%, Minimum  89.99% using method 11
Number of false positives with core edit > 0 is 614
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: 'HL_45175.1'
                     Signature: {'cWW-cWS-F-F'}
                         NumNT: 6
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 5
                      Truncate: [0×1 double]
                      NumFixed: 14
                      OwnScore: [-7.8600 -8.8155 -7.1333 -8.2319 -10.7059]
                   OwnSequence: {'CAGUUGGUAG'  'CAGUCGGUAG'  'CAGUGGUAG'  'CAGGGGUAG'  'UAAUGGUCAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10 9 9 10]
            MeanSequenceLength: 9.6000
               DeficitEditData: [4111×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

5 sequences from 3D structures
Using 4111 random sequences, 0 from an alignment, and 5 from 3D structures
Group 110, HL_45175.1  has acceptance rules AlignmentScore >= -27.1333, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  22.7908
TP   100.00%, TN    96.01%, min    96.01%,   5 3D sequences,     0 alignment sequences, 4111 random sequences,  164 random matches,  6 NTs, cWW-cWS-F-F
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 <= 15.6574
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: 'HL_45785.1'
                     Signature: {'cWW-F-F-F-F-cSH-F-F'}
                         NumNT: 10
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 1
                         NumBR: 2
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 28
                      OwnScore: [-6.5157 -6.5157]
                   OwnSequence: {'GUUCCCUCACC'  'GUUCCCUCACC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11]
            MeanSequenceLength: 11
               DeficitEditData: [984×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 984 random sequences, 0 from an alignment, and 2 from 3D structures
Group 111, HL_45785.1  has acceptance rules AlignmentScore >= -26.5157, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.0582
TP   100.00%, TN    96.04%, min    96.04%,   2 3D sequences,     0 alignment sequences,  984 random sequences,   39 random matches, 10 NTs, cWW-F-F-F-F-cSH-F-F
Sensitivity 100.00%, Specificity  96.04%, Minimum  96.04% using method 6
Number of false positives with core edit > 0 is 39
1 * Deficit + 3 * Core Edit <= 19.5425
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_46501.1'
                     Signature: {'cWW-cWS'}
                         NumNT: 5
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 12
                      OwnScore: [-5.0171 -4.3240]
                   OwnSequence: {'CUGAAG'  'CUUAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 5]
            MeanSequenceLength: 5.5000
               DeficitEditData: [5594×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 5594 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 112, HL_46501.1  has acceptance rules AlignmentScore >= -24.3240, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.8240
TP   100.00%, TN    87.12%, min    87.12%,   2 3D sequences,     0 alignment sequences, 5558 random sequences,  716 random matches,  5 NTs, cWW-cWS
Sensitivity 100.00%, Specificity  87.12%, Minimum  87.12% using method 11
Number of false positives with core edit > 0 is 716
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: 'HL_47732.1'
                     Signature: {'cWW-F-F-F-F-F-F'}
                         NumNT: 8
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 24
                      OwnScore: [-6.8596 -6.8596]
                   OwnSequence: {'CAAAAUAACAAG'  'CAAAAUAACAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [12 12]
            MeanSequenceLength: 12
               DeficitEditData: [1415×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 1415 random sequences, 0 from an alignment, and 2 from 3D structures
Group 113, HL_47732.1  has acceptance rules AlignmentScore >= -26.8596, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  23.2142
TP   100.00%, TN    95.97%, min    95.97%,   2 3D sequences,     0 alignment sequences, 1415 random sequences,   57 random matches,  8 NTs, cWW-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.97%, Minimum  95.97% using method 6
Number of false positives with core edit > 0 is 57
1 * Deficit + 3 * Core Edit <= 16.3545
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_47787.2'
                     Signature: {'cWW-F-F-F-F'}
                         NumNT: 6
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 1
                         NumBR: 2
                  NumInstances: 10
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: [-4.8232 -4.8232 -3.7245 -3.7245 -5.4778 -3.7245 -4.3792 -3.7245 -10.8023 -10.4576]
                   OwnSequence: {'CAUCCCG'  'CAUUCCG'  'CAUGCCG'  'CAUGCCG'  'CGUUCG'  'CAUGCCG'  'CGUCCG'  'CAUGCCG'  'CAUUUUGG'  'UGAAAA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 7 7 7 6 7 6 7 8 6]
            MeanSequenceLength: 6.8000
               DeficitEditData: [5439×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

10 sequences from 3D structures
Using 5439 random sequences, 0 from an alignment, and 10 from 3D structures
Group 114, HL_47787.2  has acceptance rules AlignmentScore >= -23.7245, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.6703
TP   100.00%, TN    96.01%, min    96.01%,  10 3D sequences,     0 alignment sequences, 5382 random sequences,  215 random matches,  6 NTs, cWW-F-F-F-F
Sensitivity 100.00%, Specificity  96.01%, Minimum  96.01% using method 6
Number of false positives with core edit > 0 is 215
1 * Deficit + 3 * Core Edit <= 9.9457
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: 'HL_47854.1'
                     Signature: {'cWW-F-F-F-F'}
                         NumNT: 6
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: -4.9116
                   OwnSequence: {'GAAAGACC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 8
            MeanSequenceLength: 8
               DeficitEditData: [5134×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 5134 random sequences, 0 from an alignment, and 1 from 3D structures
Group 115, HL_47854.1  has acceptance rules AlignmentScore >= -24.9116, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.2820
TP   100.00%, TN    95.81%, min    95.81%,   1 3D sequences,     0 alignment sequences, 5134 random sequences,  215 random matches,  6 NTs, cWW-F-F-F-F
Sensitivity 100.00%, Specificity  95.81%, Minimum  95.81% using method 6
Number of false positives with core edit > 0 is 215
1 * Deficit + 3 * Core Edit <= 12.3703
Motif index 1


ans = 

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

                       MotifID: 'HL_48417.5'
                     Signature: {'cWW-F-F'}
                         NumNT: 4
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 26
                      Truncate: [0×1 double]
                      NumFixed: 14
                      OwnScore: [-7.8613 -8.1208 -7.8613 -9.0248 -7.0184 -7.0184 -8.5240 -7.3628 -8.0256 -14.3895 -7.3628 -7.9739 … ]
                   OwnSequence: {1×26 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 7 7 7 6 6 7 6 6 11 6 6 7 6 7 6 5 7 6 7 10 6 6 7 7 7]
            MeanSequenceLength: 6.7692
               DeficitEditData: [8528×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

26 sequences from 3D structures
Using 8528 random sequences, 0 from an alignment, and 26 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, HL_48417.5  has acceptance rules AlignmentScore >= -25.9356, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.4356
TP   100.00%, TN    79.33%, min    79.33%,  26 3D sequences,     0 alignment sequences, 8458 random sequences, 1748 random matches,  4 NTs, cWW-F-F
Sensitivity 100.00%, Specificity  79.33%, Minimum  79.33% using method 11
Number of false positives with core edit > 0 is 1748
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


ans = 

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

                       MotifID: 'HL_48778.2'
                     Signature: {'cWW-F'}
                         NumNT: 3
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 2
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 46
                      Truncate: [0×1 double]
                      NumFixed: 10
                      OwnScore: [-7.4979 -3.2002 -5.9571 -5.2416 -3.2002 -3.2002 -3.2002 -3.2002 -6.2004 -6.3278 -6.4422 -4.3863 -6.2896 … ]
                   OwnSequence: {1×46 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [5 4 5 4 4 4 4 4 5 5 5 4 4 5 4 4 4 4 4 5 5 5 4 5 6 4 4 4 6 4 4 5 4 5 5 6 6 5 4 4 5 5 6 5 4 5]
            MeanSequenceLength: 4.6087
               DeficitEditData: [4706×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

46 sequences from 3D structures
Using 4706 random sequences, 0 from an alignment, and 46 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 117, HL_48778.2  has acceptance rules AlignmentScore >= -23.2002, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  12.7002
TP   100.00%, TN    67.10%, min    67.10%,  46 3D sequences,     0 alignment sequences, 3881 random sequences, 1277 random matches,  3 NTs, cWW-F
Sensitivity 100.00%, Specificity  67.10%, Minimum  67.10% using method 11
Number of false positives with core edit > 0 is 1277
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


ans = 

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

                       MotifID: 'HL_49922.4'
                     Signature: {'cWW-F-F-F'}
                         NumNT: 5
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 10
                      Truncate: [0×1 double]
                      NumFixed: 12
                      OwnScore: [-4.0597 -4.0597 -4.0597 -4.0597 -4.0597 -4.0597 -7.6476 -7.6476 -8.6809 -8.5792]
                   OwnSequence: {'UAGUAA'  'UAGUAA'  'UAGUAA'  'UAGUAA'  'UAGUAA'  'UAGUAA'  'CAAAAUG'  'CAAAAUG'  'GUAAUCC'  'CUUAUCG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 6 6 6 6 7 7 7 7]
            MeanSequenceLength: 6.4000
               DeficitEditData: [6119×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

10 sequences from 3D structures
Using 6119 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 118, HL_49922.4  has acceptance rules AlignmentScore >= -24.0597, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.5597
TP   100.00%, TN    95.09%, min    95.09%,  10 3D sequences,     0 alignment sequences, 6113 random sequences,  300 random matches,  5 NTs, cWW-F-F-F
Sensitivity 100.00%, Specificity  95.09%, Minimum  95.09% using method 11
Number of false positives with core edit > 0 is 300
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: 'HL_49941.1'
                     Signature: {'cWW-F-F-F-F-F'}
                         NumNT: 7
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 4
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: [-8.0731 -8.0731 -9.5394 -9.9368]
                   OwnSequence: {'CAGGUGGUUAG'  'CAGGUGGUUAG'  'CAGCUGGUCAG'  'CAGCCUGGUAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11 11 11]
            MeanSequenceLength: 11
               DeficitEditData: [2266×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 2266 random sequences, 0 from an alignment, and 4 from 3D structures
Group 119, HL_49941.1  has acceptance rules AlignmentScore >= -28.0731, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.1714
TP   100.00%, TN    95.98%, min    95.98%,   4 3D sequences,     0 alignment sequences, 2266 random sequences,   91 random matches,  7 NTs, cWW-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.98%, Minimum  95.98% using method 6
Number of false positives with core edit > 0 is 91
1 * Deficit + 3 * Core Edit <= 18.0983
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: 'HL_50006.2'
                     Signature: {'cWW-F-F'}
                         NumNT: 4
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 5
                      Truncate: [0×1 double]
                      NumFixed: 12
                      OwnScore: [-8.3285 -8.3285 -9.0098 -8.2327 -12.9544]
                   OwnSequence: {'CCUUUCACG'  'CCUUUCACG'  'CGAAAG'  'CUUCGG'  'GAAGGAUC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 6 6 8]
            MeanSequenceLength: 7.6000
               DeficitEditData: [7905×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

5 sequences from 3D structures
Using 7905 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 120, HL_50006.2  has acceptance rules AlignmentScore >= -28.2327, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.7327
TP   100.00%, TN    81.03%, min    81.03%,   5 3D sequences,     0 alignment sequences, 7859 random sequences, 1491 random matches,  4 NTs, cWW-F-F
Sensitivity 100.00%, Specificity  81.03%, Minimum  81.03% using method 11
Number of false positives with core edit > 0 is 1491
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: 'HL_50318.1'
                     Signature: {'cWW-cSH-F-F'}
                         NumNT: 6
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: -6.0162
                   OwnSequence: {'CGUUAAUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 8
            MeanSequenceLength: 8
               DeficitEditData: [6916×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 6916 random sequences, 0 from an alignment, and 1 from 3D structures
Group 121, HL_50318.1  has acceptance rules AlignmentScore >= -26.0162, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  18.4634
TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences, 6916 random sequences,  277 random matches,  6 NTs, cWW-cSH-F-F
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 277
1 * Deficit + 3 * Core Edit <= 12.4472
Motif index 1


ans = 

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

                       MotifID: 'HL_50418.1'
                     Signature: {'cWW-F-F-F-F-F-F-F-F-F'}
                         NumNT: 11
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 3
                      Truncate: [0×1 double]
                      NumFixed: 26
                      OwnScore: [-8.9410 -8.9410 -11.5485]
                   OwnSequence: {'GAAGCAGGCAC'  'GAAGCCUCCAC'  'CUGGAGAUACG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11 11]
            MeanSequenceLength: 11
               DeficitEditData: [2195×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 2195 random sequences, 0 from an alignment, and 3 from 3D structures
Group 122, HL_50418.1  has acceptance rules AlignmentScore >= -28.9410, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.0072
TP   100.00%, TN    95.95%, min    95.95%,   3 3D sequences,     0 alignment sequences, 2195 random sequences,   89 random matches, 11 NTs, cWW-F-F-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.95%, Minimum  95.95% using method 6
Number of false positives with core edit > 0 is 89
1 * Deficit + 3 * Core Edit <= 16.0662
Motif index 1
Motif index 2
Motif index 3


ans = 

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

                       MotifID: 'HL_50537.6'
                     Signature: {'cWW-F-F-F'}
                         NumNT: 5
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 4
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: [-8.0931 -8.0828 -10.4137 -9.9237]
                   OwnSequence: {'ACUGUUAAU'  'GCUGUUAAC'  'CUUGUCGCG'  'CCAGUUAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 9 8]
            MeanSequenceLength: 8.7500
               DeficitEditData: [7957×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 7957 random sequences, 0 from an alignment, and 4 from 3D structures
Group 123, HL_50537.6  has acceptance rules AlignmentScore >= -28.0828, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  19.3618
TP   100.00%, TN    96.00%, min    96.00%,   4 3D sequences,     0 alignment sequences, 7957 random sequences,  318 random matches,  5 NTs, cWW-F-F-F
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 318
1 * Deficit + 3 * Core Edit <= 11.2790
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: 'HL_50779.4'
                     Signature: {'cWW-F-F-F-F-F-F-F'}
                         NumNT: 9
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 2
                  NumInstances: 4
                      Truncate: [0×1 double]
                      NumFixed: 22
                      OwnScore: [-5.5842 -5.5842 -5.0734 -5.0734]
                   OwnSequence: {'GAAGCAACGC'  'GAUGCAACGC'  'GACUCAACAC'  'GACUCAACAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10 10 10]
            MeanSequenceLength: 10
               DeficitEditData: [2505×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 2505 random sequences, 0 from an alignment, and 4 from 3D structures
Group 124, HL_50779.4  has acceptance rules AlignmentScore >= -25.0734, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  22.6922
TP   100.00%, TN    95.97%, min    95.97%,   4 3D sequences,     0 alignment sequences, 2505 random sequences,  101 random matches,  9 NTs, cWW-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.97%, Minimum  95.97% using method 6
Number of false positives with core edit > 0 is 101
1 * Deficit + 3 * Core Edit <= 17.6188
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: 'HL_50851.1'
                     Signature: {'cWW-cWH-cWH-cWH-cWH-F'}
                         NumNT: 9
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 24
                      OwnScore: -4.5507
                   OwnSequence: {'GAGGCGGUUGGU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 12
            MeanSequenceLength: 12
               DeficitEditData: [251×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 251 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  24.2223 because the cutoff seemed overly generous
Group 125, HL_50851.1  has acceptance rules AlignmentScore >= -24.5507, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.7576
TP   100.00%, TN    98.01%, min    98.01%,   1 3D sequences,     0 alignment sequences,  251 random sequences,    5 random matches,  9 NTs, cWW-cWH-cWH-cWH-cWH-F
Sensitivity 100.00%, Specificity  98.01%, Minimum  98.01% using method 8
Number of false positives with core edit > 0 is 5
1 * Deficit + 3 * Core Edit <= 22.2069
Motif index 1


ans = 

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

                       MotifID: 'HL_50860.2'
                     Signature: {'cWW-F-cWH-F-F-F-F'}
                         NumNT: 9
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 6
                      Truncate: [0×1 double]
                      NumFixed: 26
                      OwnScore: [-6.3188 -6.7443 -4.6324 -4.8976 -4.8976 -6.5195]
                   OwnSequence: {'GUCGGACAU'  'GACAGAGAC'  'GACGGAAAU'  'AACAGAAAU'  'AACAGAAAU'  'GUUGGAAAU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 9 9 9 9]
            MeanSequenceLength: 9
               DeficitEditData: [4696×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

6 sequences from 3D structures
Using 4696 random sequences, 0 from an alignment, and 6 from 3D structures
Group 126, HL_50860.2  has acceptance rules AlignmentScore >= -24.6324, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  20.6942
TP   100.00%, TN    96.00%, min    96.00%,   6 3D sequences,     0 alignment sequences, 4696 random sequences,  188 random matches,  9 NTs, cWW-F-cWH-F-F-F-F
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 188
1 * Deficit + 3 * Core Edit <= 16.0618
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: 'HL_51447.1'
                     Signature: {'cWW-F-F-F-F-F'}
                         NumNT: 7
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: -4.9961
                   OwnSequence: {'CGAGUCG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 7
            MeanSequenceLength: 7
               DeficitEditData: [3902×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 3902 random sequences, 0 from an alignment, and 1 from 3D structures
Group 127, HL_51447.1  has acceptance rules AlignmentScore >= -24.9961, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.5850
TP   100.00%, TN    95.98%, min    95.98%,   1 3D sequences,     0 alignment sequences, 3901 random sequences,  157 random matches,  7 NTs, cWW-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.98%, Minimum  95.98% using method 6
Number of false positives with core edit > 0 is 157
1 * Deficit + 3 * Core Edit <= 11.5889
Motif index 1


ans = 

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

                       MotifID: 'HL_51921.1'
                     Signature: {'cWW-tSH-tSS-tHS-F-F-F-F-F-F-F-F-F-F-F'}
                         NumNT: 18
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 16
                        NumBPh: 1
                         NumBR: 4
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 48
                      OwnScore: [-12.2799 -12.2799]
                   OwnSequence: {'UGAAUUGCAGAUAUUCGUGAA'  'UGAAUUGCAGAAUUCCGUGAA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [21 21]
            MeanSequenceLength: 21
               DeficitEditData: [3×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 3 random sequences, 0 from an alignment, and 2 from 3D structures
Group 128, HL_51921.1  has acceptance rules AlignmentScore >= -32.2799, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  37.2799
TP   100.00%, TN   100.00%, min   100.00%,   2 3D sequences,     0 alignment sequences,    3 random sequences,    0 random matches, 18 NTs, cWW-tSH-tSS-tHS-F-F-F-F-F-F-F-F-F-F-F
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


ans = 

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

                       MotifID: 'HL_52953.3'
                     Signature: {'cWW-F-F-F-F'}
                         NumNT: 6
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 9
                      Truncate: [0×1 double]
                      NumFixed: 16
                      OwnScore: [-4.2010 -4.2010 -6.2864 -5.6255 -5.7337 -5.7337 -4.2010 -5.1147 -5.1147]
                   OwnSequence: {'GGAAAC'  'GGAAAC'  'GAGUAC'  'CGAGUG'  'CAAUGG'  'CAAUGG'  'GGAAAC'  'CGUGAG'  'CGUGAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 6 6 6 6 6 6 6]
            MeanSequenceLength: 6
               DeficitEditData: [3945×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

9 sequences from 3D structures
Using 3945 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 129, HL_52953.3  has acceptance rules AlignmentScore >= -24.2010, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.7010
TP   100.00%, TN    87.85%, min    87.85%,   9 3D sequences,     0 alignment sequences, 3894 random sequences,  473 random matches,  6 NTs, cWW-F-F-F-F
Sensitivity 100.00%, Specificity  87.85%, Minimum  87.85% using method 11
Number of false positives with core edit > 0 is 473
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: 'HL_53454.2'
                     Signature: {'cWW-tSH-F-F-F-F-F'}
                         NumNT: 9
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 6
                      Truncate: [0×1 double]
                      NumFixed: 24
                      OwnScore: [-8.1449 -8.9840 -8.1449 -9.5371 -14.8564 -14.8564]
                   OwnSequence: {'CGUGUGGAAG'  'CGCAUGGAAG'  'CGUGUGGAAG'  'UGAAUGGAAG'  'UAUCGGUUAGAG'  'UAUCGGUUAGAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10 10 10 12 12]
            MeanSequenceLength: 10.6667
               DeficitEditData: [4453×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

6 sequences from 3D structures
Using 4453 random sequences, 0 from an alignment, and 6 from 3D structures
Group 130, HL_53454.2  has acceptance rules AlignmentScore >= -28.1449, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  23.1972
TP   100.00%, TN    95.98%, min    95.98%,   6 3D sequences,     0 alignment sequences, 4453 random sequences,  179 random matches,  9 NTs, cWW-tSH-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.98%, Minimum  95.98% using method 6
Number of false positives with core edit > 0 is 179
1 * Deficit + 3 * Core Edit <= 15.0523
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: 'HL_53504.3'
                     Signature: {'cWW-tSH-F-F-F-F-F-F'}
                         NumNT: 10
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 28
                      OwnScore: [-9.9934 -9.3433]
                   OwnSequence: {'CGAAGUCAUAAG'  'GGAAAUGAAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [12 10]
            MeanSequenceLength: 11
               DeficitEditData: [4604×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 4604 random sequences, 0 from an alignment, and 2 from 3D structures
Group 131, HL_53504.3  has acceptance rules AlignmentScore >= -29.3433, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  22.7004
TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 4604 random sequences,  184 random matches, 10 NTs, cWW-tSH-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 184
1 * Deficit + 3 * Core Edit <= 13.3570
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_53890.2'
                     Signature: {'cWW-F-F-F'}
                         NumNT: 5
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 15
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: [-6.1324 -6.5001 -6.1324 -7.1505 -7.7383 -6.6303 -8.5230 -8.6097 -8.5230 -8.1221 -8.6041 -8.8319 -9.5913 … ]
                   OwnSequence: {1×15 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 6 6 6 6 7 7 7 6 6 7 6 7 6]
            MeanSequenceLength: 6.3333
               DeficitEditData: [6747×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

15 sequences from 3D structures
Using 6747 random sequences, 0 from an alignment, and 15 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 132, HL_53890.2  has acceptance rules AlignmentScore >= -26.1324, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.6324
TP   100.00%, TN    70.39%, min    70.39%,  15 3D sequences,     0 alignment sequences, 6626 random sequences, 1962 random matches,  5 NTs, cWW-F-F-F
Sensitivity 100.00%, Specificity  70.39%, Minimum  70.39% using method 11
Number of false positives with core edit > 0 is 1962
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


ans = 

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

                       MotifID: 'HL_55195.3'
                     Signature: {'cWW-F'}
                         NumNT: 3
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 0
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 6
                      Truncate: [0×1 double]
                      NumFixed: 10
                      OwnScore: [-3.0127 -3.0127 -3.0127 -3.9000 -6.7332 -6.4978]
                   OwnSequence: {'UUUAGG'  'UUUAGG'  'UUUAGG'  'UUGAGG'  'UCGAAG'  'GGUAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 6 6 6 5]
            MeanSequenceLength: 5.8333
               DeficitEditData: [4947×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

6 sequences from 3D structures
Using 4947 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 133, HL_55195.3  has acceptance rules AlignmentScore >= -23.0127, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  12.5127
TP   100.00%, TN    89.67%, min    89.67%,   6 3D sequences,     0 alignment sequences, 4916 random sequences,  508 random matches,  3 NTs, cWW-F
Sensitivity 100.00%, Specificity  89.67%, Minimum  89.67% using method 11
Number of false positives with core edit > 0 is 508
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: 'HL_55305.1'
                     Signature: {'cWW-F-F-F-F-F'}
                         NumNT: 5
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 16
                      OwnScore: [-9.4071 -9.4071]
                   OwnSequence: {'UCUAUGAUACCA'  'UCUAUGAUACCA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [12 12]
            MeanSequenceLength: 12
               DeficitEditData: [867×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 867 random sequences, 0 from an alignment, and 2 from 3D structures
Group 134, HL_55305.1  has acceptance rules AlignmentScore >= -29.4071, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  27.1692
TP   100.00%, TN    95.96%, min    95.96%,   2 3D sequences,     0 alignment sequences,  867 random sequences,   35 random matches,  5 NTs, cWW-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.96%, Minimum  95.96% using method 6
Number of false positives with core edit > 0 is 35
1 * Deficit + 3 * Core Edit <= 17.7621
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_55436.1'
                     Signature: {'cWW-F-F-F-F-F-F-F-F'}
                         NumNT: 10
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 4
                      Truncate: [0×1 double]
                      NumFixed: 22
                      OwnScore: [-8.8565 -8.0736 -8.1573 -10.9256]
                   OwnSequence: {'GGUCCCAGAC'  'UCUGCGAGGA'  'ACGGGGAGUU'  'UCAGAGGACA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10 10 10]
            MeanSequenceLength: 10
               DeficitEditData: [3497×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 3497 random sequences, 0 from an alignment, and 4 from 3D structures
Group 135, HL_55436.1  has acceptance rules AlignmentScore >= -28.0736, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.5566
TP   100.00%, TN    96.00%, min    96.00%,   4 3D sequences,     0 alignment sequences, 3497 random sequences,  140 random matches, 10 NTs, cWW-F-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 140
1 * Deficit + 3 * Core Edit <= 16.4830
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: 'HL_56131.2'
                     Signature: {'cWW-F-F'}
                         NumNT: 4
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 6
                      Truncate: [0×1 double]
                      NumFixed: 14
                      OwnScore: [-10.4435 -10.0394 -7.2099 -7.2099 -8.3177 -9.2682]
                   OwnSequence: {'GCUGCGAAC'  'CCUCCUAAG'  'UACUAUA'  'UACUAUA'  'GGUC'  'UUGCG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 7 7 4 5]
            MeanSequenceLength: 6.8333
               DeficitEditData: [7723×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

6 sequences from 3D structures
Using 7723 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 136, HL_56131.2  has acceptance rules AlignmentScore >= -27.2099, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.7099
TP   100.00%, TN    68.39%, min    68.39%,   6 3D sequences,     0 alignment sequences, 7614 random sequences, 2407 random matches,  4 NTs, cWW-F-F
Sensitivity 100.00%, Specificity  68.39%, Minimum  68.39% using method 11
Number of false positives with core edit > 0 is 2407
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: 'HL_56334.1'
                     Signature: {'cWW-F'}
                         NumNT: 3
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 2
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 16
                      Truncate: [0×1 double]
                      NumFixed: 10
                      OwnScore: [-7.1719 -8.0374 -6.0258 -5.1222 -5.1222 -5.1867 -7.7415 -8.0374 -5.4770 -5.1867 -5.1867 -5.4770 -5.1867 … ]
                   OwnSequence: {1×16 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [5 6 5 5 5 5 6 6 6 5 5 6 5 6 6 6]
            MeanSequenceLength: 5.5000
               DeficitEditData: [5102×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

16 sequences from 3D structures
Using 5102 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 137, HL_56334.1  has acceptance rules AlignmentScore >= -25.1222, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  14.6222
TP   100.00%, TN    57.50%, min    57.50%,  16 3D sequences,     0 alignment sequences, 5023 random sequences, 2135 random matches,  3 NTs, cWW-F
Sensitivity 100.00%, Specificity  57.50%, Minimum  57.50% using method 11
Number of false positives with core edit > 0 is 2135
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: 'HL_56676.1'
                     Signature: {'cWW-F-F'}
                         NumNT: 6
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 14
                      OwnScore: [-5.2134 -4.4762]
                   OwnSequence: {'UGUAAG'  'CUUCGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6]
            MeanSequenceLength: 6
               DeficitEditData: [5283×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 5283 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 138, HL_56676.1  has acceptance rules AlignmentScore >= -24.4762, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.9762
TP   100.00%, TN    94.45%, min    94.45%,   2 3D sequences,     0 alignment sequences, 5266 random sequences,  292 random matches,  6 NTs, cWW-F-F
Sensitivity 100.00%, Specificity  94.45%, Minimum  94.45% using method 11
Number of false positives with core edit > 0 is 292
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: 'HL_57176.2'
                     Signature: {'cWW-F-F-F'}
                         NumNT: 5
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 14
                      Truncate: [0×1 double]
                      NumFixed: 14
                      OwnScore: [-7.6116 -5.5987 -5.5987 -5.5987 -5.8351 -7.1008 -6.2418 -5.8351 -6.2418 -5.9685 -7.8081 -5.9685 -5.9685 … ]
                   OwnSequence: {1×14 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 7 7 7 7 7 7 7 7 6 6 6 6 6]
            MeanSequenceLength: 6.6429
               DeficitEditData: [4997×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

14 sequences from 3D structures
Using 4997 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 139, HL_57176.2  has acceptance rules AlignmentScore >= -25.5987, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.0987
TP   100.00%, TN    84.01%, min    84.01%,  14 3D sequences,     0 alignment sequences, 4983 random sequences,  797 random matches,  5 NTs, cWW-F-F-F
Sensitivity 100.00%, Specificity  84.01%, Minimum  84.01% using method 11
Number of false positives with core edit > 0 is 797
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: 'HL_57863.1'
                     Signature: {'cWW-F-F-cWH-cWH-F'}
                         NumNT: 8
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 22
                      OwnScore: [-5.7114 -5.0183]
                   OwnSequence: {'GAAGGAGGUC'  'GAGGAGGUC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 9]
            MeanSequenceLength: 9.5000
               DeficitEditData: [4047×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 4047 random sequences, 0 from an alignment, and 2 from 3D structures
Group 140, HL_57863.1  has acceptance rules AlignmentScore >= -25.0183, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  22.5596
TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 4047 random sequences,  162 random matches,  8 NTs, cWW-F-F-cWH-cWH-F
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 162
1 * Deficit + 3 * Core Edit <= 17.5413
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_57875.1'
                     Signature: {'cWW-F-F'}
                         NumNT: 4
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 5
                      Truncate: [0×1 double]
                      NumFixed: 14
                      OwnScore: [-5.5231 -9.6864 -6.7271 -6.0902 -7.1214]
                   OwnSequence: {'GGUUUC'  'GUGAAGC'  'UGUAGG'  'CAUUAG'  'AAUUAUU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 7 6 6 7]
            MeanSequenceLength: 6.4000
               DeficitEditData: [6049×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

5 sequences from 3D structures
Using 6049 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 141, HL_57875.1  has acceptance rules AlignmentScore >= -25.5231, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.0231
TP   100.00%, TN    82.70%, min    82.70%,   5 3D sequences,     0 alignment sequences, 6024 random sequences, 1042 random matches,  4 NTs, cWW-F-F
Sensitivity 100.00%, Specificity  82.70%, Minimum  82.70% using method 11
Number of false positives with core edit > 0 is 1042
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: 'HL_58224.1'
                     Signature: {'cWW-F-F-F-F-F'}
                         NumNT: 7
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 22
                      OwnScore: -6.6948
                   OwnSequence: {'CAGUCGGUAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 10
            MeanSequenceLength: 10
               DeficitEditData: [3316×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 3316 random sequences, 0 from an alignment, and 1 from 3D structures
Group 142, HL_58224.1  has acceptance rules AlignmentScore >= -26.6948, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.1879
TP   100.00%, TN    95.93%, min    95.93%,   1 3D sequences,     0 alignment sequences, 3316 random sequences,  135 random matches,  7 NTs, cWW-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.93%, Minimum  95.93% using method 6
Number of false positives with core edit > 0 is 135
1 * Deficit + 3 * Core Edit <= 17.4931
Motif index 1


ans = 

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

                       MotifID: 'HL_58539.1'
                     Signature: {'cWW-tWS-F-tHW-F-F-F-F-F-F-F-F'}
                         NumNT: 13
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 36
                      OwnScore: -10.4256
                   OwnSequence: {'UUAAAUUGGGCACUUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 16
            MeanSequenceLength: 16
               DeficitEditData: [25×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 25 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  21.3658 because the cutoff seemed overly generous
Group 143, HL_58539.1  has acceptance rules AlignmentScore >= -30.4256, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  31.3203
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences,   25 random sequences,    1 random matches, 13 NTs, cWW-tWS-F-tHW-F-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 8
Number of false positives with core edit > 0 is 1
1 * Deficit + 3 * Core Edit <= 20.8947
Motif index 1


ans = 

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

                       MotifID: 'HL_59330.1'
                     Signature: {'cWW-F-F-F-F-F'}
                         NumNT: 7
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 2
                        NumBPh: 0
                         NumBR: 2
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: -4.4306
                   OwnSequence: {'UUCUGCGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 8
            MeanSequenceLength: 8
               DeficitEditData: [3636×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 3636 random sequences, 0 from an alignment, and 1 from 3D structures
Group 144, HL_59330.1  has acceptance rules AlignmentScore >= -24.4306, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  20.2376
TP   100.00%, TN    95.96%, min    95.96%,   1 3D sequences,     0 alignment sequences, 3636 random sequences,  147 random matches,  7 NTs, cWW-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.96%, Minimum  95.96% using method 6
Number of false positives with core edit > 0 is 147
1 * Deficit + 3 * Core Edit <= 15.8070
Motif index 1


ans = 

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

                       MotifID: 'HL_59564.1'
                     Signature: {'cWW-F-cSS-F-cSS-F-F-F-F-F-F-F-F-F-F-F-F'}
                         NumNT: 20
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 15
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 44
                      OwnScore: -15.5353
                   OwnSequence: {'UGGCCUUUCUUAAAAAAAAA'}
                  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 145, HL_59564.1  has acceptance rules AlignmentScore >= -35.5353, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  40.5353
TP   100.00%, TN   100.00%, min   100.00%,   1 3D sequences,     0 alignment sequences,    4 random sequences,    0 random matches, 20 NTs, cWW-F-cSS-F-cSS-F-F-F-F-F-F-F-F-F-F-F-F
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: 'HL_59735.5'
                     Signature: {'cWW-F-F-F-F-F'}
                         NumNT: 7
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: [-5.6748 -5.3444]
                   OwnSequence: {'CAAUAGG'  'UGAAAUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 7]
            MeanSequenceLength: 7
               DeficitEditData: [4033×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 4033 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 146, HL_59735.5  has acceptance rules AlignmentScore >= -25.3444, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  14.8444
TP   100.00%, TN    93.84%, min    93.84%,   2 3D sequences,     0 alignment sequences, 4029 random sequences,  248 random matches,  7 NTs, cWW-F-F-F-F-F
Sensitivity 100.00%, Specificity  93.84%, Minimum  93.84% using method 11
Number of false positives with core edit > 0 is 248
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: 'HL_59843.1'
                     Signature: {'cWW-F-F-F-F'}
                         NumNT: 6
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 14
                      OwnScore: [-6.7238 -5.7478]
                   OwnSequence: {'UCAAUGA'  'CGAGAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 6]
            MeanSequenceLength: 6.5000
               DeficitEditData: [6604×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 6604 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 147, HL_59843.1  has acceptance rules AlignmentScore >= -25.7478, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.2478
TP   100.00%, TN    91.05%, min    91.05%,   2 3D sequences,     0 alignment sequences, 6593 random sequences,  590 random matches,  6 NTs, cWW-F-F-F-F
Sensitivity 100.00%, Specificity  91.05%, Minimum  91.05% using method 11
Number of false positives with core edit > 0 is 590
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: 'HL_60266.1'
                     Signature: {'cWW-cWW-tWH-F-F-F-F'}
                         NumNT: 9
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 10
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 16
                      OwnScore: [-8.2590 -9.7442]
                   OwnSequence: {'GGAUAAAAGAC'  'GUUUACCAAAAUC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 13]
            MeanSequenceLength: 12
               DeficitEditData: [3471×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 3471 random sequences, 0 from an alignment, and 2 from 3D structures
Group 148, HL_60266.1  has acceptance rules AlignmentScore >= -28.2590, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.1739
TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 3471 random sequences,  139 random matches,  9 NTs, cWW-cWW-tWH-F-F-F-F
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 139
1 * Deficit + 3 * Core Edit <= 15.9149
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_60293.1'
                     Signature: {'cWW-cWH-F-cWH-cHW-cHW-cWH-cHW-cWH-F-cWH-cWH-cWH-F'}
                         NumNT: 18
                  NumBasepairs: 12
                    Structured: 1
                     NumStacks: 18
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 46
                      OwnScore: [-8.3980 -8.3980]
                   OwnSequence: {'UGUGGAAGGAGUGGCUGGGUUG'  'UGUGGAAGGAGUGGCUGGGUUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [22 22]
            MeanSequenceLength: 22
               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 149, HL_60293.1  has acceptance rules AlignmentScore >= -28.3980, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  33.3980
TP   100.00%, TN      NaN%, min   100.00%,   2 3D sequences,     0 alignment sequences,    0 random sequences,    0 random matches, 18 NTs, cWW-cWH-F-cWH-cHW-cHW-cWH-cHW-cWH-F-cWH-cWH-cWH-F
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: 'HL_60914.1'
                     Signature: {'cWW-F'}
                         NumNT: 3
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 0
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 10
                      OwnScore: -3.2509
                   OwnSequence: {'CUGGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 5
            MeanSequenceLength: 5
               DeficitEditData: [4689×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 4689 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 150, HL_60914.1  has acceptance rules AlignmentScore >= -23.2509, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  12.7509
TP   100.00%, TN    85.07%, min    85.07%,   1 3D sequences,     0 alignment sequences, 4670 random sequences,  697 random matches,  3 NTs, cWW-F
Sensitivity 100.00%, Specificity  85.07%, Minimum  85.07% using method 11
Number of false positives with core edit > 0 is 697
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: 'HL_61996.2'
                     Signature: {'cWW-tWH-F-F-F'}
                         NumNT: 7
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 2
                         NumBR: 0
                  NumInstances: 8
                      Truncate: [0×1 double]
                      NumFixed: 20
                      OwnScore: [-5.8170 -5.8170 -5.8170 -8.5563 -7.5516 -7.3531 -7.3531 -11.8382]
                   OwnSequence: {1×8 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10 10 10 10 10 10 9]
            MeanSequenceLength: 9.8750
               DeficitEditData: [5482×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

8 sequences from 3D structures
Using 5482 random sequences, 0 from an alignment, and 8 from 3D structures
Group 151, HL_61996.2  has acceptance rules AlignmentScore >= -25.8170, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  21.6337
TP   100.00%, TN    96.01%, min    96.01%,   8 3D sequences,     0 alignment sequences, 5482 random sequences,  219 random matches,  7 NTs, cWW-tWH-F-F-F
Sensitivity 100.00%, Specificity  96.01%, Minimum  96.01% using method 6
Number of false positives with core edit > 0 is 219
1 * Deficit + 3 * Core Edit <= 15.8167
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: 'HL_62934.1'
                     Signature: {'cWW-tSH-F'}
                         NumNT: 6
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 14
                      OwnScore: [-6.1497 -5.4339]
                   OwnSequence: {'CGCAUAG'  'CAACCG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 6]
            MeanSequenceLength: 6.5000
               DeficitEditData: [6513×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 6513 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 152, HL_62934.1  has acceptance rules AlignmentScore >= -25.4339, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  14.9339
TP   100.00%, TN    92.96%, min    92.96%,   2 3D sequences,     0 alignment sequences, 6510 random sequences,  458 random matches,  6 NTs, cWW-tSH-F
Sensitivity 100.00%, Specificity  92.96%, Minimum  92.96% using method 11
Number of false positives with core edit > 0 is 458
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: 'HL_63355.1'
                     Signature: {'cWW-F-F-F-F-F-F-F-F-F-F-F'}
                         NumNT: 13
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 3
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 30
                      OwnScore: -7.7878
                   OwnSequence: {'GCUUAGAAGCAGCC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 14
            MeanSequenceLength: 14
               DeficitEditData: [198×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 198 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  23.6978 because the cutoff seemed overly generous
Group 153, HL_63355.1  has acceptance rules AlignmentScore >= -27.7878, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  30.6123
TP   100.00%, TN    97.98%, min    97.98%,   1 3D sequences,     0 alignment sequences,  198 random sequences,    4 random matches, 13 NTs, cWW-F-F-F-F-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  97.98%, Minimum  97.98% using method 8
Number of false positives with core edit > 0 is 4
1 * Deficit + 3 * Core Edit <= 22.8245
Motif index 1


ans = 

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

                       MotifID: 'HL_64292.1'
                     Signature: {'cWW-F-F-F-F-F-F-F-F'}
                         NumNT: 10
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 26
                      OwnScore: [-15.8767 -18.6220]
                   OwnSequence: {'GGGCCCAUUCGGGUCU'  'CGGAUCAGUCACCCAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [16 17]
            MeanSequenceLength: 16.5000
               DeficitEditData: [35×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 35 random sequences, 0 from an alignment, and 2 from 3D structures
Group 154, HL_64292.1  has acceptance rules AlignmentScore >= -35.8767, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  32.0587
TP   100.00%, TN    97.14%, min    97.14%,   2 3D sequences,     0 alignment sequences,   35 random sequences,    1 random matches, 10 NTs, cWW-F-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  97.14%, Minimum  97.14% using method 6
Number of false positives with core edit > 0 is 1
1 * Deficit + 3 * Core Edit <= 16.1819
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_64690.6'
                     Signature: {'cWW-cSW-F-F-F-F'}
                         NumNT: 8
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 9
                      Truncate: [0×1 double]
                      NumFixed: 20
                      OwnScore: [-6.4251 -7.2136 -7.5237 -7.2136 -7.6094 -7.0129 -9.5778 -13.1726 -13.4526]
                   OwnSequence: {1×9 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 9 9 9 9 9 9 9]
            MeanSequenceLength: 9
               DeficitEditData: [6361×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

9 sequences from 3D structures
Using 6361 random sequences, 0 from an alignment, and 9 from 3D structures
Group 155, HL_64690.6  has acceptance rules AlignmentScore >= -26.4251, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  19.2464
TP   100.00%, TN    95.99%, min    95.99%,   9 3D sequences,     0 alignment sequences, 6361 random sequences,  255 random matches,  8 NTs, cWW-cSW-F-F-F-F
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 <= 12.8213
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: 'HL_65313.1'
                     Signature: {'cWW-F-F-F'}
                         NumNT: 5
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 1
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 14
                      OwnScore: -4.3904
                   OwnSequence: {'CCUUUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 6
            MeanSequenceLength: 6
               DeficitEditData: [4389×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 4389 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 156, HL_65313.1  has acceptance rules AlignmentScore >= -24.3904, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.8904
TP   100.00%, TN    92.02%, min    92.02%,   1 3D sequences,     0 alignment sequences, 4387 random sequences,  350 random matches,  5 NTs, cWW-F-F-F
Sensitivity 100.00%, Specificity  92.02%, Minimum  92.02% using method 11
Number of false positives with core edit > 0 is 350
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: 'HL_65794.5'
                     Signature: {'cWW-F-F-F-F'}
                         NumNT: 6
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 14
                      Truncate: [0×1 double]
                      NumFixed: 16
                      OwnScore: [-6.1827 -6.1827 -6.1478 -5.5730 -4.4744 -6.6195 -4.4744 -5.3760 -9.6310 -8.5890 -9.0671 -8.4038 -9.3184 … ]
                   OwnSequence: {1×14 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 6 6 6 6 6 6 6 7 7 7 7 7]
            MeanSequenceLength: 6.3571
               DeficitEditData: [5178×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

14 sequences from 3D structures
Using 5178 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 157, HL_65794.5  has acceptance rules AlignmentScore >= -24.4744, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.9744
TP   100.00%, TN    88.49%, min    88.49%,  14 3D sequences,     0 alignment sequences, 5107 random sequences,  588 random matches,  6 NTs, cWW-F-F-F-F
Sensitivity 100.00%, Specificity  88.49%, Minimum  88.49% using method 11
Number of false positives with core edit > 0 is 588
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: 'HL_66103.1'
                     Signature: {'cWW-F-F'}
                         NumNT: 4
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 14
                      OwnScore: [-6.7883 -6.7883]
                   OwnSequence: {'CGCAUAG'  'CUUCGUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 7]
            MeanSequenceLength: 7
               DeficitEditData: [7038×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 7038 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 158, HL_66103.1  has acceptance rules AlignmentScore >= -26.7883, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.2883
TP   100.00%, TN    92.50%, min    92.50%,   2 3D sequences,     0 alignment sequences, 7038 random sequences,  528 random matches,  4 NTs, cWW-F-F
Sensitivity 100.00%, Specificity  92.50%, Minimum  92.50% using method 11
Number of false positives with core edit > 0 is 528
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: 'HL_66482.1'
                     Signature: {'cWW-cWW-tWW-F-F-tWH-F-F-F-F-F-F-F-F'}
                         NumNT: 18
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 16
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 38
                      OwnScore: -11.3758
                   OwnSequence: {'CCAUCCGAGUUGCAAGAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 18
            MeanSequenceLength: 18
               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 159, HL_66482.1  has acceptance rules AlignmentScore >= -31.3758, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  36.3758
TP   100.00%, TN   100.00%, min   100.00%,   1 3D sequences,     0 alignment sequences,    5 random sequences,    0 random matches, 18 NTs, cWW-cWW-tWW-F-F-tWH-F-F-F-F-F-F-F-F
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: 'HL_66853.7'
                     Signature: {'cWW-cWS-F-cSH'}
                         NumNT: 7
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 2
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 11
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: [-8.3513 -8.3513 -8.3513 -8.3513 -8.6784 -8.3513 -7.3434 -9.0324 -11.3030 -7.3434 -7.3434]
                   OwnSequence: {1×11 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10 10 10 9 10 9 10 11 9 9]
            MeanSequenceLength: 9.7273
               DeficitEditData: [5319×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

11 sequences from 3D structures
Using 5319 random sequences, 0 from an alignment, and 11 from 3D structures
Group 160, HL_66853.7  has acceptance rules AlignmentScore >= -27.3434, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  23.7167
TP   100.00%, TN    96.00%, min    96.00%,  11 3D sequences,     0 alignment sequences, 5319 random sequences,  213 random matches,  7 NTs, cWW-cWS-F-cSH
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 213
1 * Deficit + 3 * Core Edit <= 16.3733
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: 'HL_67079.1'
                     Signature: {'cWW-F-F-F-F-F-F-F'}
                         NumNT: 9
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 4
                      Truncate: [0×1 double]
                      NumFixed: 28
                      OwnScore: [-11.5500 -13.8067 -10.6132 -10.6132]
                   OwnSequence: {'GGUUCGAAUCC'  'CAACUCUACCG'  'AUUGUAAUUAUU'  'AUUGUAAUUGUU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11 12 12]
            MeanSequenceLength: 11.5000
               DeficitEditData: [4812×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 4812 random sequences, 0 from an alignment, and 4 from 3D structures
Group 161, HL_67079.1  has acceptance rules AlignmentScore >= -30.6132, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.5596
TP   100.00%, TN    96.01%, min    96.01%,   4 3D sequences,     0 alignment sequences, 4812 random sequences,  192 random matches,  9 NTs, cWW-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.01%, Minimum  96.01% using method 6
Number of false positives with core edit > 0 is 192
1 * Deficit + 3 * Core Edit <= 15.9464
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: 'HL_67407.5'
                     Signature: {'cWW-F-F-F-F-F-F-F-F'}
                         NumNT: 10
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 10
                      Truncate: [0×1 double]
                      NumFixed: 26
                      OwnScore: [-7.7390 -8.2185 -7.1199 -8.2185 -12.0415 -8.6945 -7.7390 -10.6716 -9.2053 -8.6945]
                   OwnSequence: {1×10 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11 11 11 11 11 11 11 11 11]
            MeanSequenceLength: 11
               DeficitEditData: [2233×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

10 sequences from 3D structures
Using 2233 random sequences, 0 from an alignment, and 10 from 3D structures
Group 162, HL_67407.5  has acceptance rules AlignmentScore >= -27.1199, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.6907
TP   100.00%, TN    95.97%, min    95.97%,  10 3D sequences,     0 alignment sequences, 2233 random sequences,   90 random matches, 10 NTs, cWW-F-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.97%, Minimum  95.97% using method 6
Number of false positives with core edit > 0 is 90
1 * Deficit + 3 * Core Edit <= 19.5708
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: 'HL_67667.2'
                     Signature: {'cWW-F-F'}
                         NumNT: 4
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 1
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 3
                      Truncate: [0×1 double]
                      NumFixed: 12
                      OwnScore: [-4.3941 -4.3941 -4.3941]
                   OwnSequence: {'CUGUUCG'  'CUGUUCG'  'CUGUUCG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 7 7]
            MeanSequenceLength: 7
               DeficitEditData: [3709×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 3709 random sequences, 0 from an alignment, and 3 from 3D structures
Group 163, HL_67667.2  has acceptance rules AlignmentScore >= -24.3941, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.0866
TP   100.00%, TN    95.98%, min    95.98%,   3 3D sequences,     0 alignment sequences, 3708 random sequences,  149 random matches,  4 NTs, cWW-F-F
Sensitivity 100.00%, Specificity  95.98%, Minimum  95.98% using method 6
Number of false positives with core edit > 0 is 149
1 * Deficit + 3 * Core Edit <= 10.6925
Motif index 1
Motif index 2
Motif index 3


ans = 

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

                       MotifID: 'HL_68257.1'
                     Signature: {'cWW-F-F-F-F-F-F-F-F'}
                         NumNT: 11
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 13
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: [-13.4155 -9.0016]
                   OwnSequence: {'AAACGCUUGCGUUU'  'UGAAUCCAUAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [14 11]
            MeanSequenceLength: 12.5000
               DeficitEditData: [2105×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 2105 random sequences, 0 from an alignment, and 2 from 3D structures
Group 164, HL_68257.1  has acceptance rules AlignmentScore >= -29.0016, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  27.1131
TP   100.00%, TN    96.01%, min    96.01%,   2 3D sequences,     0 alignment sequences, 2105 random sequences,   84 random matches, 11 NTs, cWW-F-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.01%, Minimum  96.01% using method 6
Number of false positives with core edit > 0 is 84
1 * Deficit + 3 * Core Edit <= 18.1115
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_68572.1'
                     Signature: {'cWW-F-F-F-F-F-F-F'}
                         NumNT: 9
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 3
                      Truncate: [0×1 double]
                      NumFixed: 24
                      OwnScore: [-14.1290 -14.3563 -14.4066]
                   OwnSequence: {'CGGAGCGGCUGAAG'  'UCAGUCUGGCAGAG'  'CUCAGCAGGUAGAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [14 14 14]
            MeanSequenceLength: 14
               DeficitEditData: [656×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 656 random sequences, 0 from an alignment, and 3 from 3D structures
Group 165, HL_68572.1  has acceptance rules AlignmentScore >= -34.1290, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  30.8156
TP   100.00%, TN    96.04%, min    96.04%,   3 3D sequences,     0 alignment sequences,  656 random sequences,   26 random matches,  9 NTs, cWW-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.04%, Minimum  96.04% using method 6
Number of false positives with core edit > 0 is 26
1 * Deficit + 3 * Core Edit <= 16.6867
Motif index 1
Motif index 2
Motif index 3


ans = 

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

                       MotifID: 'HL_68767.1'
                     Signature: {'cWW-cWS-tSH-cWS-F'}
                         NumNT: 8
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 1
                         NumBR: 2
                  NumInstances: 3
                      Truncate: [0×1 double]
                      NumFixed: 20
                      OwnScore: [-9.3938 -8.2952 -11.0720]
                   OwnSequence: {'GGAAUCGGUAGAC'  'GGAAUGGGUAGAC'  'GAAAUCGGUAAAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [13 13 13]
            MeanSequenceLength: 13
               DeficitEditData: [756×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 756 random sequences, 0 from an alignment, and 3 from 3D structures
Group 166, HL_68767.1  has acceptance rules AlignmentScore >= -28.2952, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  27.1806
TP   100.00%, TN    96.03%, min    96.03%,   3 3D sequences,     0 alignment sequences,  756 random sequences,   30 random matches,  8 NTs, cWW-cWS-tSH-cWS-F
Sensitivity 100.00%, Specificity  96.03%, Minimum  96.03% using method 6
Number of false positives with core edit > 0 is 30
1 * Deficit + 3 * Core Edit <= 18.8854
Motif index 1
Motif index 2
Motif index 3


ans = 

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

                       MotifID: 'HL_69139.1'
                     Signature: {'cWW-F-F-F-F-F-F-F-F'}
                         NumNT: 9
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 28
                      OwnScore: [-10.0077 -13.0189]
                   OwnSequence: {'UCUUUUAUUG'  'AGCACGUGAAAUU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 13]
            MeanSequenceLength: 11.5000
               DeficitEditData: [2864×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 2864 random sequences, 0 from an alignment, and 2 from 3D structures
Group 167, HL_69139.1  has acceptance rules AlignmentScore >= -30.0077, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.1722
TP   100.00%, TN    95.98%, min    95.98%,   2 3D sequences,     0 alignment sequences, 2864 random sequences,  115 random matches,  9 NTs, cWW-F-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.98%, Minimum  95.98% using method 6
Number of false positives with core edit > 0 is 115
1 * Deficit + 3 * Core Edit <= 15.1646
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_69752.2'
                     Signature: {'cWW-F'}
                         NumNT: 3
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 2
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 7
                      Truncate: [0×1 double]
                      NumFixed: 10
                      OwnScore: [-6.4912 -6.4912 -6.4912 -6.4912 -6.1635 -6.1635 -5.4738]
                   OwnSequence: {'CUAAGUG'  'CUAAGUG'  'CUAAGUG'  'CUAAGUG'  'CUGUUG'  'CUGUUG'  'CUUAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 7 7 7 6 6 5]
            MeanSequenceLength: 6.4286
               DeficitEditData: [5979×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

7 sequences from 3D structures
Using 5979 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 168, HL_69752.2  has acceptance rules AlignmentScore >= -25.4738, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  14.9738
TP   100.00%, TN    76.63%, min    76.63%,   7 3D sequences,     0 alignment sequences, 5952 random sequences, 1391 random matches,  3 NTs, cWW-F
Sensitivity 100.00%, Specificity  76.63%, Minimum  76.63% using method 11
Number of false positives with core edit > 0 is 1391
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: 'HL_70658.1'
                     Signature: {'cWW-F-F-F-F-F-F-F-F-F'}
                         NumNT: 12
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 13
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 24
                      OwnScore: [-10.7751 -11.6769]
                   OwnSequence: {'AAUGGGAUGUCGU'  'AGUAACUAUGACU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [13 13]
            MeanSequenceLength: 13
               DeficitEditData: [1367×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 1367 random sequences, 0 from an alignment, and 2 from 3D structures
Group 169, HL_70658.1  has acceptance rules AlignmentScore >= -30.7751, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  29.8989
TP   100.00%, TN    95.98%, min    95.98%,   2 3D sequences,     0 alignment sequences, 1367 random sequences,   55 random matches, 12 NTs, cWW-F-F-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.98%, Minimum  95.98% using method 6
Number of false positives with core edit > 0 is 55
1 * Deficit + 3 * Core Edit <= 19.1238
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_70751.1'
                     Signature: {'cWW-F-F-F-F-F-F-F-F-F'}
                         NumNT: 11
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 2
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 26
                      OwnScore: -6.7470
                   OwnSequence: {'CAAUAUCGAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 11
            MeanSequenceLength: 11
               DeficitEditData: [1236×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 1236 random sequences, 0 from an alignment, and 1 from 3D structures
Group 170, HL_70751.1  has acceptance rules AlignmentScore >= -26.7470, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.8254
TP   100.00%, TN    95.87%, min    95.87%,   1 3D sequences,     0 alignment sequences, 1236 random sequences,   51 random matches, 11 NTs, cWW-F-F-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.87%, Minimum  95.87% using method 6
Number of false positives with core edit > 0 is 51
1 * Deficit + 3 * Core Edit <= 18.0784
Motif index 1


ans = 

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

                       MotifID: 'HL_70782.2'
                     Signature: {'cWW-F'}
                         NumNT: 3
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 0
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 4
                      Truncate: [0×1 double]
                      NumFixed: 10
                      OwnScore: [-7.2380 -7.2380 -7.7912 -6.6747]
                   OwnSequence: {'CCUCAG'  'CCUCAG'  'GUGUCC'  'UUUAA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 6 5]
            MeanSequenceLength: 5.7500
               DeficitEditData: [6288×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 6288 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 171, HL_70782.2  has acceptance rules AlignmentScore >= -26.6747, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.1747
TP   100.00%, TN    62.65%, min    62.65%,   4 3D sequences,     0 alignment sequences, 6263 random sequences, 2339 random matches,  3 NTs, cWW-F
Sensitivity 100.00%, Specificity  62.65%, Minimum  62.65% using method 11
Number of false positives with core edit > 0 is 2339
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: 'HL_71391.1'
                     Signature: {'cWW-F-F-F-F'}
                         NumNT: 5
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 12
                      OwnScore: [-4.7712 -3.7990]
                   OwnSequence: {'GGGAAC'  'GUUCAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6]
            MeanSequenceLength: 6
               DeficitEditData: [5427×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 5427 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 172, HL_71391.1  has acceptance rules AlignmentScore >= -23.7990, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.2990
TP   100.00%, TN    93.24%, min    93.24%,   2 3D sequences,     0 alignment sequences, 5414 random sequences,  366 random matches,  5 NTs, cWW-F-F-F-F
Sensitivity 100.00%, Specificity  93.24%, Minimum  93.24% using method 11
Number of false positives with core edit > 0 is 366
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: 'HL_72628.1'
                     Signature: {'cWW-tSH-F-F-F-F'}
                         NumNT: 8
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: -5.6175
                   OwnSequence: {'CGACAUAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 9
            MeanSequenceLength: 9
               DeficitEditData: [4825×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 4825 random sequences, 0 from an alignment, and 1 from 3D structures
Group 173, HL_72628.1  has acceptance rules AlignmentScore >= -25.6175, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  19.1918
TP   100.00%, TN    95.92%, min    95.92%,   1 3D sequences,     0 alignment sequences, 4825 random sequences,  197 random matches,  8 NTs, cWW-tSH-F-F-F-F
Sensitivity 100.00%, Specificity  95.92%, Minimum  95.92% using method 6
Number of false positives with core edit > 0 is 197
1 * Deficit + 3 * Core Edit <= 13.5743
Motif index 1


ans = 

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

                       MotifID: 'HL_73183.1'
                     Signature: {'cWW-tSH-tHW-F-F-F-F-F-F-F-F-F'}
                         NumNT: 14
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 16
                        NumBPh: 2
                         NumBR: 1
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 34
                      OwnScore: [-11.4890 -10.2221]
                   OwnSequence: {'CGAAAAAAUUGGAAGUAG'  'UGAAGGCAGAAGUAA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [18 15]
            MeanSequenceLength: 16.5000
               DeficitEditData: [282×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 282 random sequences, 0 from an alignment, and 2 from 3D structures
Group 174, HL_73183.1  has acceptance rules AlignmentScore >= -30.2221, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  29.6788
TP   100.00%, TN    96.10%, min    96.10%,   2 3D sequences,     0 alignment sequences,  282 random sequences,   11 random matches, 14 NTs, cWW-tSH-tHW-F-F-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.10%, Minimum  96.10% using method 6
Number of false positives with core edit > 0 is 11
1 * Deficit + 3 * Core Edit <= 19.4567
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_73247.1'
                     Signature: {'cWW-F-tWH-F-F-F-F-F-F-F-F-F-F'}
                         NumNT: 15
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 11
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 3
                      Truncate: [0×1 double]
                      NumFixed: 48
                      OwnScore: [-8.5750 -8.5750 -8.5392]
                   OwnSequence: {'CAUACACGAGUUGCAAG'  'CAUACACGAGUUGCAAG'  'CAUCCGAGUUGCAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [17 17 15]
            MeanSequenceLength: 16.3333
               DeficitEditData: [73×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 73 random sequences, 0 from an alignment, and 3 from 3D structures
Decreased cutoff from  23.6660 because the cutoff seemed overly generous
Group 175, HL_73247.1  has acceptance rules AlignmentScore >= -28.5392, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  31.1828
TP   100.00%, TN    98.63%, min    98.63%,   3 3D sequences,     0 alignment sequences,   73 random sequences,    1 random matches, 15 NTs, cWW-F-tWH-F-F-F-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  98.63%, Minimum  98.63% using method 8
Number of false positives with core edit > 0 is 1
1 * Deficit + 3 * Core Edit <= 22.6436
Motif index 1
Motif index 2
Motif index 3


ans = 

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

                       MotifID: 'HL_73255.1'
                     Signature: {'cWW-F-F-F-F-F-F'}
                         NumNT: 6
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: [-7.7360 -10.0102]
                   OwnSequence: {'CAGCACUUUG'  'CAGCUACUCG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10]
            MeanSequenceLength: 10
               DeficitEditData: [2891×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 2891 random sequences, 0 from an alignment, and 2 from 3D structures
Group 176, HL_73255.1  has acceptance rules AlignmentScore >= -27.7360, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  23.0145
TP   100.00%, TN    95.99%, min    95.99%,   2 3D sequences,     0 alignment sequences, 2891 random sequences,  116 random matches,  6 NTs, cWW-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 116
1 * Deficit + 3 * Core Edit <= 15.2785
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_73266.9'
                     Signature: {'cWW-F-F-cSW-cSH-F'}
                         NumNT: 9
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 13
                      Truncate: [0×1 double]
                      NumFixed: 22
                      OwnScore: [-4.7945 -4.7945 -5.0534 -4.7945 -5.0534 -4.7945 -4.7945 -4.7945 -5.0534 -5.4461 -5.4296 -5.4315 -5.4154]
                   OwnSequence: {1×13 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 9 9 9 9 9 9 9 9 9 9 9]
            MeanSequenceLength: 9
               DeficitEditData: [3923×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

13 sequences from 3D structures
Using 3923 random sequences, 0 from an alignment, and 13 from 3D structures
Group 177, HL_73266.9  has acceptance rules AlignmentScore >= -24.7945, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  19.2795
TP   100.00%, TN    96.00%, min    96.00%,  13 3D sequences,     0 alignment sequences, 3923 random sequences,  157 random matches,  9 NTs, cWW-F-F-cSW-cSH-F
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 <= 14.4850
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: 'HL_73916.1'
                     Signature: {'cWW-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F'}
                         NumNT: 37
                  NumBasepairs: 5
                    Structured: 1
                     NumStacks: 27
                        NumBPh: 1
                         NumBR: 3
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 98
                      OwnScore: -26.3197
                   OwnSequence: {'AUAGCUCAGUCGGUAGAGCAGGGGAUUGAAAAUUCCGAGU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 40
            MeanSequenceLength: 40
               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 178, HL_73916.1  has acceptance rules AlignmentScore >= -46.3197, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  51.3197
TP   100.00%, TN      NaN%, min   100.00%,   1 3D sequences,     0 alignment sequences,    0 random sequences,    0 random matches, 37 NTs, cWW-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F
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: 'HL_74055.2'
                     Signature: {'cWW-tWH-cWH-tSH-tHW-tHW-tSW'}
                         NumNT: 13
                  NumBasepairs: 8
                    Structured: 1
                     NumStacks: 15
                        NumBPh: 1
                         NumBR: 2
                  NumInstances: 7
                      Truncate: [0×1 double]
                      NumFixed: 28
                      OwnScore: [-6.1388 -6.2905 -6.1388 -6.1388 -7.0750 -7.0750 -6.1388]
                   OwnSequence: {1×7 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [15 15 15 15 15 15 15]
            MeanSequenceLength: 15
               DeficitEditData: [97×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

7 sequences from 3D structures
Using 97 random sequences, 0 from an alignment, and 7 from 3D structures
Decreased cutoff from  22.8176 because the cutoff seemed overly generous
Group 179, HL_74055.2  has acceptance rules AlignmentScore >= -26.1388, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  28.0183
TP   100.00%, TN    97.94%, min    97.94%,   7 3D sequences,     0 alignment sequences,   97 random sequences,    2 random matches, 13 NTs, cWW-tWH-cWH-tSH-tHW-tHW-tSW
Sensitivity 100.00%, Specificity  97.94%, Minimum  97.94% using method 8
Number of false positives with core edit > 0 is 2
1 * Deficit + 3 * Core Edit <= 21.8795
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: 'HL_74292.1'
                     Signature: {'cWW-F-F-F-F-F-F-F-F'}
                         NumNT: 10
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 24
                      OwnScore: -7.0758
                   OwnSequence: {'GCAAGGAGAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 10
            MeanSequenceLength: 10
               DeficitEditData: [1971×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 1971 random sequences, 0 from an alignment, and 1 from 3D structures
Group 180, HL_74292.1  has acceptance rules AlignmentScore >= -27.0758, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  23.4702
TP   100.00%, TN    95.13%, min    95.13%,   1 3D sequences,     0 alignment sequences, 1971 random sequences,   96 random matches, 10 NTs, cWW-F-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.13%, Minimum  95.13% using method 6
Number of false positives with core edit > 0 is 96
1 * Deficit + 3 * Core Edit <= 16.3944
Motif index 1


ans = 

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

                       MotifID: 'HL_74379.3'
                     Signature: {'cWW-F-F-cSS-cSS-F-F-F'}
                         NumNT: 9
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 22
                      OwnScore: [-9.4399 -9.4399]
                   OwnSequence: {'GCAAGGUUAACC'  'GCAAGGUUAACC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [12 12]
            MeanSequenceLength: 12
               DeficitEditData: [991×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 991 random sequences, 0 from an alignment, and 2 from 3D structures
Group 181, HL_74379.3  has acceptance rules AlignmentScore >= -29.4399, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  29.3831
TP   100.00%, TN    95.96%, min    95.96%,   2 3D sequences,     0 alignment sequences,  991 random sequences,   40 random matches,  9 NTs, cWW-F-F-cSS-cSS-F-F-F
Sensitivity 100.00%, Specificity  95.96%, Minimum  95.96% using method 6
Number of false positives with core edit > 0 is 40
1 * Deficit + 3 * Core Edit <= 19.9432
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_75293.5'
                     Signature: {'cWW-F-F-F-F-F-F-F-F'}
                         NumNT: 10
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 2
                         NumBR: 0
                  NumInstances: 11
                      Truncate: [0×1 double]
                      NumFixed: 26
                      OwnScore: [-8.3134 -8.6036 -8.6036 -8.3134 -9.9106 -8.5505 -9.9106 -8.5505 -11.2889 -9.8823 -14.7366]
                   OwnSequence: {1×11 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10 10 10 11 11 11 11 10 10 10]
            MeanSequenceLength: 10.3636
               DeficitEditData: [5526×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

11 sequences from 3D structures
Using 5526 random sequences, 0 from an alignment, and 11 from 3D structures
Group 182, HL_75293.5  has acceptance rules AlignmentScore >= -28.3134, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  23.2722
TP   100.00%, TN    96.00%, min    96.00%,  11 3D sequences,     0 alignment sequences, 5526 random sequences,  221 random matches, 10 NTs, cWW-F-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 221
1 * Deficit + 3 * Core Edit <= 14.9588
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: 'HL_75660.5'
                     Signature: {'cWW-F'}
                         NumNT: 3
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 2
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 19
                      Truncate: [0×1 double]
                      NumFixed: 10
                      OwnScore: [-6.0531 -4.8164 -4.9539 -8.3526 -4.9539 -6.0295 -5.3059 -6.8003 -4.5368 -6.1670 -7.4459 -7.9849 -9.2616 … ]
                   OwnSequence: {1×19 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [5 5 5 6 5 6 5 5 5 6 6 6 7 6 6 5 5 5 6]
            MeanSequenceLength: 5.5263
               DeficitEditData: [5788×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

19 sequences from 3D structures
Using 5788 random sequences, 0 from an alignment, and 19 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 183, HL_75660.5  has acceptance rules AlignmentScore >= -24.5368, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  14.0368
TP   100.00%, TN    61.35%, min    61.35%,  19 3D sequences,     0 alignment sequences, 5586 random sequences, 2159 random matches,  3 NTs, cWW-F
Sensitivity 100.00%, Specificity  61.35%, Minimum  61.35% using method 11
Number of false positives with core edit > 0 is 2159
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


ans = 

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

                       MotifID: 'HL_76094.1'
                     Signature: {'cWW-cWS-F-F'}
                         NumNT: 5
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: -2.8581
                   OwnSequence: {'CAAUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 5
            MeanSequenceLength: 5
               DeficitEditData: [3146×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 3146 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 184, HL_76094.1  has acceptance rules AlignmentScore >= -22.8581, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  12.3581
TP   100.00%, TN    87.81%, min    87.81%,   1 3D sequences,     0 alignment sequences, 3133 random sequences,  382 random matches,  5 NTs, cWW-cWS-F-F
Sensitivity 100.00%, Specificity  87.81%, Minimum  87.81% using method 11
Number of false positives with core edit > 0 is 382
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: 'HL_77082.1'
                     Signature: {'cWW-F-F-F-F-F-F'}
                         NumNT: 8
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 8
                      Truncate: [0×1 double]
                      NumFixed: 22
                      OwnScore: [-7.5076 -8.0559 -9.9778 -8.6955 -11.9364 -7.9409 -10.4475 -10.4475]
                   OwnSequence: {'CCGAAAAG'  'ACUCUAAAU'  'ACUCAUACU'  'UCUGUAAAA'  'GUUUCGAC'  'GCCAUCAC'  'GUUAUCUUU'  'GUUAUCUUU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 9 9 9 8 8 9 9]
            MeanSequenceLength: 8.6250
               DeficitEditData: [6461×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

8 sequences from 3D structures
Using 6461 random sequences, 0 from an alignment, and 8 from 3D structures
Group 185, HL_77082.1  has acceptance rules AlignmentScore >= -27.5076, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  18.6303
TP   100.00%, TN    96.00%, min    96.00%,   8 3D sequences,     0 alignment sequences, 6456 random sequences,  258 random matches,  8 NTs, cWW-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 258
1 * Deficit + 3 * Core Edit <= 11.1227
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: 'HL_77436.5'
                     Signature: {'cWW-F-F-F-F-F'}
                         NumNT: 7
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 23
                      Truncate: [0×1 double]
                      NumFixed: 20
                      OwnScore: [-6.5169 -6.5169 -6.5169 -6.5169 -6.2451 -6.2451 -13.4307 -13.4307 -7.2361 -8.1459 -8.1459 -8.4384 … ]
                   OwnSequence: {1×23 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8 8 8 8 8 10 10 8 8 8 8 8 8 7 8 9 9 9 8 9 9 8]
            MeanSequenceLength: 8.3478
               DeficitEditData: [7951×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

23 sequences from 3D structures
Using 7951 random sequences, 0 from an alignment, and 23 from 3D structures
Group 186, HL_77436.5  has acceptance rules AlignmentScore >= -26.2451, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.9558
TP   100.00%, TN    95.98%, min    95.98%,  23 3D sequences,     0 alignment sequences, 7941 random sequences,  319 random matches,  7 NTs, cWW-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.98%, Minimum  95.98% using method 6
Number of false positives with core edit > 0 is 319
1 * Deficit + 3 * Core Edit <= 9.7107
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


ans = 

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

                       MotifID: 'HL_77600.2'
                     Signature: {'cWW-F-F-F-F-F'}
                         NumNT: 7
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 10
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: [-10.4822 -10.4822 -11.9173 -12.5472 -9.7460 -11.2817 -13.3997 -9.8045 -12.2322 -13.4670]
                   OwnSequence: {1×10 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10 10 10 9 9 9 9 9 10]
            MeanSequenceLength: 9.5000
               DeficitEditData: [4906×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

10 sequences from 3D structures
Using 4906 random sequences, 0 from an alignment, and 10 from 3D structures
Group 187, HL_77600.2  has acceptance rules AlignmentScore >= -29.7460, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  19.9653
TP   100.00%, TN    96.00%, min    96.00%,  10 3D sequences,     0 alignment sequences, 4906 random sequences,  196 random matches,  7 NTs, cWW-F-F-F-F-F
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 <= 10.2193
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: 'HL_78197.1'
                     Signature: {'cWW-F-F-F-F-F-F'}
                         NumNT: 8
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 5
                      Truncate: [0×1 double]
                      NumFixed: 22
                      OwnScore: [-7.7357 -7.7357 -9.9411 -11.1777 -10.5603]
                   OwnSequence: {'GGUUGGCC'  'GGUGAGCC'  'GCGAUCAC'  'CGUUGAAAAG'  'UUAUCUUA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8 8 10 8]
            MeanSequenceLength: 8.4000
               DeficitEditData: [6492×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

5 sequences from 3D structures
Using 6492 random sequences, 0 from an alignment, and 5 from 3D structures
Group 188, HL_78197.1  has acceptance rules AlignmentScore >= -27.7357, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  18.0938
TP   100.00%, TN    95.84%, min    95.84%,   5 3D sequences,     0 alignment sequences, 6491 random sequences,  270 random matches,  8 NTs, cWW-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.84%, Minimum  95.84% using method 6
Number of false positives with core edit > 0 is 270
1 * Deficit + 3 * Core Edit <= 10.3581
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: 'HL_78284.1'
                     Signature: {'cWW-F-F-F-F-F-F-F-F-F-F'}
                         NumNT: 10
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 26
                      OwnScore: [-10.7410 -13.5816]
                   OwnSequence: {'UUCAGAGAUGAG'  'GACCUAGAUCACCC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [12 14]
            MeanSequenceLength: 13
               DeficitEditData: [1851×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 1851 random sequences, 0 from an alignment, and 2 from 3D structures
Group 189, HL_78284.1  has acceptance rules AlignmentScore >= -30.7410, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  28.5777
TP   100.00%, TN    95.95%, min    95.95%,   2 3D sequences,     0 alignment sequences, 1851 random sequences,   75 random matches, 10 NTs, cWW-F-F-F-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.95%, Minimum  95.95% using method 6
Number of false positives with core edit > 0 is 75
1 * Deficit + 3 * Core Edit <= 17.8367
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_78347.4'
                     Signature: {'cWW-F-F-F-F'}
                         NumNT: 6
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 9
                      Truncate: [0×1 double]
                      NumFixed: 14
                      OwnScore: [-10.8443 -10.8443 -10.8443 -13.3006 -14.9507 -11.5688 -11.5688 -8.0569 -9.9924]
                   OwnSequence: {1×9 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11 11 10 9 9 9 6 6]
            MeanSequenceLength: 9.1111
               DeficitEditData: [8497×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

9 sequences from 3D structures
Using 8497 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 190, HL_78347.4  has acceptance rules AlignmentScore >= -28.0569, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.5569
TP   100.00%, TN    95.86%, min    95.86%,   9 3D sequences,     0 alignment sequences, 8485 random sequences,  351 random matches,  6 NTs, cWW-F-F-F-F
Sensitivity 100.00%, Specificity  95.86%, Minimum  95.86% using method 11
Number of false positives with core edit > 0 is 351
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: 'HL_78677.1'
                     Signature: {'cWW-F-F'}
                         NumNT: 3
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 0
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 10
                      OwnScore: [-3.8850 -4.9193]
                   OwnSequence: {'UUCG'  'GGUAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [4 5]
            MeanSequenceLength: 4.5000
               DeficitEditData: [4991×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 4991 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 191, HL_78677.1  has acceptance rules AlignmentScore >= -23.8850, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.3850
TP   100.00%, TN    70.30%, min    70.30%,   2 3D sequences,     0 alignment sequences, 4892 random sequences, 1453 random matches,  3 NTs, cWW-F-F
Sensitivity 100.00%, Specificity  70.30%, Minimum  70.30% using method 11
Number of false positives with core edit > 0 is 1453
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: 'HL_80008.1'
                     Signature: {'cWW-F-F-F-cSH-F'}
                         NumNT: 8
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 16
                      OwnScore: -6.4953
                   OwnSequence: {'CUUGCAAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 9
            MeanSequenceLength: 9
               DeficitEditData: [4457×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 4457 random sequences, 0 from an alignment, and 1 from 3D structures
Group 192, HL_80008.1  has acceptance rules AlignmentScore >= -26.4953, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  19.9951
TP   100.00%, TN    95.94%, min    95.94%,   1 3D sequences,     0 alignment sequences, 4457 random sequences,  181 random matches,  8 NTs, cWW-F-F-F-cSH-F
Sensitivity 100.00%, Specificity  95.94%, Minimum  95.94% using method 6
Number of false positives with core edit > 0 is 181
1 * Deficit + 3 * Core Edit <= 13.4998
Motif index 1


ans = 

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

                       MotifID: 'HL_80241.1'
                     Signature: {'cWW-F-F-F-F-F-F-F'}
                         NumNT: 9
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 22
                      OwnScore: [-6.8457 -6.8457]
                   OwnSequence: {'UGGUUUCCA'  'UGAUAUGAA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9]
            MeanSequenceLength: 9
               DeficitEditData: [3529×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 3529 random sequences, 0 from an alignment, and 2 from 3D structures
Group 193, HL_80241.1  has acceptance rules AlignmentScore >= -26.8457, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  19.7810
TP   100.00%, TN    95.95%, min    95.95%,   2 3D sequences,     0 alignment sequences, 3528 random sequences,  143 random matches,  9 NTs, cWW-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.95%, Minimum  95.95% using method 6
Number of false positives with core edit > 0 is 143
1 * Deficit + 3 * Core Edit <= 12.9353
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_80362.1'
                     Signature: {'cWW-F-F-F'}
                         NumNT: 5
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 14
                      OwnScore: -7.0681
                   OwnSequence: {'CCUCACACG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 9
            MeanSequenceLength: 9
               DeficitEditData: [3377×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 3377 random sequences, 0 from an alignment, and 1 from 3D structures
Group 194, HL_80362.1  has acceptance rules AlignmentScore >= -27.0681, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  21.1745
TP   100.00%, TN    95.97%, min    95.97%,   1 3D sequences,     0 alignment sequences, 3377 random sequences,  136 random matches,  5 NTs, cWW-F-F-F
Sensitivity 100.00%, Specificity  95.97%, Minimum  95.97% using method 6
Number of false positives with core edit > 0 is 136
1 * Deficit + 3 * Core Edit <= 14.1065
Motif index 1


ans = 

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

                       MotifID: 'HL_80411.1'
                     Signature: {'cWW-F-cSH-F-F-F-F'}
                         NumNT: 9
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 22
                      OwnScore: -8.2707
                   OwnSequence: {'CAGCCCGGUAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 11
            MeanSequenceLength: 11
               DeficitEditData: [931×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 931 random sequences, 0 from an alignment, and 1 from 3D structures
Group 195, HL_80411.1  has acceptance rules AlignmentScore >= -28.2707, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.2307
TP   100.00%, TN    96.03%, min    96.03%,   1 3D sequences,     0 alignment sequences,  931 random sequences,   37 random matches,  9 NTs, cWW-F-cSH-F-F-F-F
Sensitivity 100.00%, Specificity  96.03%, Minimum  96.03% using method 6
Number of false positives with core edit > 0 is 37
1 * Deficit + 3 * Core Edit <= 17.9599
Motif index 1


ans = 

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

                       MotifID: 'HL_80599.2'
                     Signature: {'cWW-F-F-F-F-F-F-F'}
                         NumNT: 9
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 3
                      Truncate: [0×1 double]
                      NumFixed: 20
                      OwnScore: [-5.2987 -5.2987 -9.2461]
                   OwnSequence: {'UUCAGUGUG'  'UUCAGUGUG'  'CCUUACGAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 9]
            MeanSequenceLength: 9
               DeficitEditData: [3262×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 3262 random sequences, 0 from an alignment, and 3 from 3D structures
Group 196, HL_80599.2  has acceptance rules AlignmentScore >= -25.2987, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  23.1606
TP   100.00%, TN    96.01%, min    96.01%,   3 3D sequences,     0 alignment sequences, 3262 random sequences,  130 random matches,  9 NTs, cWW-F-F-F-F-F-F-F
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 <= 17.8620
Motif index 1
Motif index 2
Motif index 3


ans = 

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

                       MotifID: 'HL_80709.3'
                     Signature: {'cWW-F-F-F'}
                         NumNT: 5
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 11
                      Truncate: [0×1 double]
                      NumFixed: 14
                      OwnScore: [-3.1784 -3.1784 -3.1784 -3.1784 -3.5462 -5.8487 -3.5462 -3.5462 -7.5915 -6.1252 -6.1252]
                   OwnSequence: {'CGCAG'  'CGCAG'  'CGCAG'  'CGCAG'  'CGAAG'  'GGAAAC'  'CGAAG'  'CGAAG'  'CUGUUG'  'CUCUUG'  'CUCUUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [5 5 5 5 5 6 5 5 6 6 6]
            MeanSequenceLength: 5.3636
               DeficitEditData: [3853×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

11 sequences from 3D structures
Using 3853 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 197, HL_80709.3  has acceptance rules AlignmentScore >= -23.1784, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  12.6784
TP   100.00%, TN    80.74%, min    80.74%,  11 3D sequences,     0 alignment sequences, 3723 random sequences,  717 random matches,  5 NTs, cWW-F-F-F
Sensitivity 100.00%, Specificity  80.74%, Minimum  80.74% using method 11
Number of false positives with core edit > 0 is 717
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: 'HL_80922.2'
                     Signature: {'cWW-tSH-F'}
                         NumNT: 5
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 3
                      Truncate: [0×1 double]
                      NumFixed: 12
                      OwnScore: [-7.5586 -11.3862 -7.9759]
                   OwnSequence: {'GAGUAUC'  'ACUACGGAU'  'CGAAUAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 9 7]
            MeanSequenceLength: 7.6667
               DeficitEditData: [7972×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 7972 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 198, HL_80922.2  has acceptance rules AlignmentScore >= -27.5586, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.0586
TP   100.00%, TN    93.40%, min    93.40%,   3 3D sequences,     0 alignment sequences, 7971 random sequences,  526 random matches,  5 NTs, cWW-tSH-F
Sensitivity 100.00%, Specificity  93.40%, Minimum  93.40% using method 11
Number of false positives with core edit > 0 is 526
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: 'HL_81100.2'
                     Signature: {'cWW'}
                         NumNT: 2
                  NumBasepairs: 1
                    Structured: 0
                     NumStacks: 0
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 3
                      Truncate: [0×1 double]
                      NumFixed: 10
                      OwnScore: [-5.9180 -5.9180 -6.1720]
                   OwnSequence: {'CGCGUG'  'CGCGUG'  'GCUUGC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 6]
            MeanSequenceLength: 6
               DeficitEditData: [3938×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 3938 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 199, HL_81100.2  has acceptance rules AlignmentScore >= -25.9180, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.4180
TP   100.00%, TN    80.51%, min    80.51%,   3 3D sequences,     0 alignment sequences, 3930 random sequences,  766 random matches,  2 NTs, cWW
Sensitivity 100.00%, Specificity  80.51%, Minimum  80.51% using method 11
Number of false positives with core edit > 0 is 766
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: 'HL_81205.3'
                     Signature: {'cWW-cWW-tWH-F-tWH-F-F-F-F-F'}
                         NumNT: 14
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 11
                        NumBPh: 3
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 32
                      OwnScore: [-5.7721 -5.7761]
                   OwnSequence: {'CACUGAGACACGGG'  'AACUGAGACACGGU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [14 14]
            MeanSequenceLength: 14
               DeficitEditData: [61×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 61 random sequences, 0 from an alignment, and 2 from 3D structures
Decreased cutoff from  23.7680 because the cutoff seemed overly generous
Group 200, HL_81205.3  has acceptance rules AlignmentScore >= -25.7721, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  28.6785
TP   100.00%, TN    98.36%, min    98.36%,   2 3D sequences,     0 alignment sequences,   61 random sequences,    1 random matches, 14 NTs, cWW-cWW-tWH-F-tWH-F-F-F-F-F
Sensitivity 100.00%, Specificity  98.36%, Minimum  98.36% using method 8
Number of false positives with core edit > 0 is 1
1 * Deficit + 3 * Core Edit <= 22.9065
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_81312.1'
                     Signature: {'cWW-F-F-F-F-F-F-F-F-F'}
                         NumNT: 10
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 28
                      OwnScore: [-6.2922 -6.2922]
                   OwnSequence: {'CAAUUUAUACAG'  'CAAUUUAUACAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [12 12]
            MeanSequenceLength: 12
               DeficitEditData: [980×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 980 random sequences, 0 from an alignment, and 2 from 3D structures
Group 201, HL_81312.1  has acceptance rules AlignmentScore >= -26.2922, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.8483
TP   100.00%, TN    95.51%, min    95.51%,   2 3D sequences,     0 alignment sequences,  980 random sequences,   44 random matches, 10 NTs, cWW-F-F-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.51%, Minimum  95.51% using method 6
Number of false positives with core edit > 0 is 44
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: 'HL_81538.2'
                     Signature: {'cWW-tSH-F-F-F-F'}
                         NumNT: 8
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 16
                      Truncate: [0×1 double]
                      NumFixed: 20
                      OwnScore: [-5.7878 -5.9647 -5.8281 -5.8281 -6.9267 -5.9647 -6.4022 -7.9185 -7.6655 -9.5194 -8.1742 -10.8398 … ]
                   OwnSequence: {1×16 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8 8 8 8 8 8 8 8 8 8 10 9 9 10 9]
            MeanSequenceLength: 8.4375
               DeficitEditData: [5849×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

16 sequences from 3D structures
Using 5849 random sequences, 0 from an alignment, and 16 from 3D structures
Group 202, HL_81538.2  has acceptance rules AlignmentScore >= -25.7878, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.4986
TP   100.00%, TN    96.00%, min    96.00%,  16 3D sequences,     0 alignment sequences, 5843 random sequences,  234 random matches,  8 NTs, cWW-tSH-F-F-F-F
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 <= 10.7108
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: 'HL_81545.2'
                     Signature: {'cWW-tWH-F-F-F-F'}
                         NumNT: 8
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 7
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: [-4.2796 -4.2796 -5.7459 -4.8674 -5.3782 -4.2796 -6.6203]
                   OwnSequence: {'GUUAAUAUUC'  'GUUAAUAUUC'  'GUUGAUAUUC'  'GUUAAGAUUC'  'GUUAAAAUUC'  'GUUAAUAUUC'  'GUCAAGAUUC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10 10 10 10 10 10]
            MeanSequenceLength: 10
               DeficitEditData: [3111×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

7 sequences from 3D structures
Using 3111 random sequences, 0 from an alignment, and 7 from 3D structures
Group 203, HL_81545.2  has acceptance rules AlignmentScore >= -24.2796, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  22.2089
TP   100.00%, TN    96.01%, min    96.01%,   7 3D sequences,     0 alignment sequences, 3109 random sequences,  124 random matches,  8 NTs, cWW-tWH-F-F-F-F
Sensitivity 100.00%, Specificity  96.01%, Minimum  96.01% using method 6
Number of false positives with core edit > 0 is 124
1 * Deficit + 3 * Core Edit <= 17.9293
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: 'HL_82710.2'
                     Signature: {'cWW-F-F-F'}
                         NumNT: 5
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 4
                      Truncate: [0×1 double]
                      NumFixed: 16
                      OwnScore: [-4.8438 -4.3329 -4.3329 -6.8748]
                   OwnSequence: {'GGGAAC'  'GGAAAC'  'GGAAAC'  'GAACUC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 6 6]
            MeanSequenceLength: 6
               DeficitEditData: [6084×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 6084 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 204, HL_82710.2  has acceptance rules AlignmentScore >= -24.3329, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.8329
TP   100.00%, TN    84.55%, min    84.55%,   4 3D sequences,     0 alignment sequences, 6034 random sequences,  932 random matches,  5 NTs, cWW-F-F-F
Sensitivity 100.00%, Specificity  84.55%, Minimum  84.55% using method 11
Number of false positives with core edit > 0 is 932
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: 'HL_83632.1'
                     Signature: {'cWW-F-F-F-F-F-F'}
                         NumNT: 8
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 6
                      Truncate: [0×1 double]
                      NumFixed: 22
                      OwnScore: [-6.5022 -6.9765 -5.5779 -5.5779 -7.3130 -5.8374]
                   OwnSequence: {'ACUCCAGAU'  'CCUGUCACG'  'ACUGUAGAU'  'ACUCUAAAU'  'CUUGCCAAG'  'ACUGAAAAU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 9 9 9 9]
            MeanSequenceLength: 9
               DeficitEditData: [4582×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

6 sequences from 3D structures
Using 4582 random sequences, 0 from an alignment, and 6 from 3D structures
Group 205, HL_83632.1  has acceptance rules AlignmentScore >= -25.5779, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  19.8095
TP   100.00%, TN    95.98%, min    95.98%,   6 3D sequences,     0 alignment sequences, 4581 random sequences,  184 random matches,  8 NTs, cWW-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.98%, Minimum  95.98% using method 6
Number of false positives with core edit > 0 is 184
1 * Deficit + 3 * Core Edit <= 14.2316
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: 'HL_83808.4'
                     Signature: {'cWW-tWW-F-F-F'}
                         NumNT: 7
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 3
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: [-5.5686 -5.9296 -5.9296]
                   OwnSequence: {'CUCCUCGCG'  'CUCCUCGCUG'  'CUCCUCGCUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 10 10]
            MeanSequenceLength: 9.6667
               DeficitEditData: [3322×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 3322 random sequences, 0 from an alignment, and 3 from 3D structures
Group 206, HL_83808.4  has acceptance rules AlignmentScore >= -25.5686, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  23.4062
TP   100.00%, TN    96.00%, min    96.00%,   3 3D sequences,     0 alignment sequences, 3322 random sequences,  133 random matches,  7 NTs, cWW-tWW-F-F-F
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 133
1 * Deficit + 3 * Core Edit <= 17.8376
Motif index 1
Motif index 2
Motif index 3


ans = 

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

                       MotifID: 'HL_84299.4'
                     Signature: {'cWW-F-F-F-F-F-F'}
                         NumNT: 8
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 9
                      Truncate: [0×1 double]
                      NumFixed: 20
                      OwnScore: [-5.3081 -5.3081 -5.8062 -6.3940 -12.9093 -5.2909 -5.2909 -5.4915 -9.9063]
                   OwnSequence: {1×9 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 9 9 9 9 9 9 9]
            MeanSequenceLength: 9
               DeficitEditData: [5358×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

9 sequences from 3D structures
Using 5358 random sequences, 0 from an alignment, and 9 from 3D structures
Group 207, HL_84299.4  has acceptance rules AlignmentScore >= -25.2909, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  19.3027
TP   100.00%, TN    96.00%, min    96.00%,   9 3D sequences,     0 alignment sequences, 5356 random sequences,  214 random matches,  8 NTs, cWW-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 214
1 * Deficit + 3 * Core Edit <= 14.0118
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: 'HL_84847.1'
                     Signature: {'cWW-F-F-F-F-tWW-F-F-F-F-F-F'}
                         NumNT: 14
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 1
                         NumBR: 2
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 44
                      OwnScore: -8.1397
                   OwnSequence: {'GUUCGCAACCAUCC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 14
            MeanSequenceLength: 14
               DeficitEditData: [193×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 193 random sequences, 0 from an alignment, and 1 from 3D structures
Decreased cutoff from  21.7086 because the cutoff seemed overly generous
Group 208, HL_84847.1  has acceptance rules AlignmentScore >= -28.1397, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  28.1690
TP   100.00%, TN    97.93%, min    97.93%,   1 3D sequences,     0 alignment sequences,  193 random sequences,    4 random matches, 14 NTs, cWW-F-F-F-F-tWW-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  97.93%, Minimum  97.93% using method 8
Number of false positives with core edit > 0 is 4
1 * Deficit + 3 * Core Edit <= 20.0294
Motif index 1


ans = 

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

                       MotifID: 'HL_85367.2'
                     Signature: {'cWW-F-F-F-F-F-F'}
                         NumNT: 8
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 11
                      Truncate: [0×1 double]
                      NumFixed: 22
                      OwnScore: [-4.7419 -4.7419 -4.7419 -4.7419 -4.7419 -4.7419 -4.7419 -9.2524 -8.4051 -12.9187 -12.9187]
                   OwnSequence: {1×11 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 9 9 9 9 9 8 8 9 9]
            MeanSequenceLength: 8.8182
               DeficitEditData: [3779×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

11 sequences from 3D structures
Using 3779 random sequences, 0 from an alignment, and 11 from 3D structures
Group 209, HL_85367.2  has acceptance rules AlignmentScore >= -24.7419, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  18.9890
TP   100.00%, TN    96.00%, min    96.00%,  11 3D sequences,     0 alignment sequences, 3778 random sequences,  151 random matches,  8 NTs, cWW-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 151
1 * Deficit + 3 * Core Edit <= 14.2472
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: 'HL_85434.1'
                     Signature: {'cWW-cWW-F-F-F-F-F-F'}
                         NumNT: 10
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 2
                         NumBR: 1
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 20
                      OwnScore: -5.5869
                   OwnSequence: {'GGUAUCCCAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 10
            MeanSequenceLength: 10
               DeficitEditData: [1697×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 1697 random sequences, 0 from an alignment, and 1 from 3D structures
Group 210, HL_85434.1  has acceptance rules AlignmentScore >= -25.5869, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.4948
TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences, 1697 random sequences,   68 random matches, 10 NTs, cWW-cWW-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 68
1 * Deficit + 3 * Core Edit <= 18.9079
Motif index 1


ans = 

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

                       MotifID: 'HL_85461.1'
                     Signature: {'cWW-F-F-F-F-F-F-F-F-F-F-F-F-F'}
                         NumNT: 15
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 2
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 42
                      OwnScore: -14.9399
                   OwnSequence: {'GGUAGCCAUUUAUGGCGAAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 20
            MeanSequenceLength: 20
               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 211, HL_85461.1  has acceptance rules AlignmentScore >= -34.9399, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  39.9399
TP   100.00%, TN    66.67%, min    66.67%,   1 3D sequences,     0 alignment sequences,    3 random sequences,    1 random matches, 15 NTs, cWW-F-F-F-F-F-F-F-F-F-F-F-F-F
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: 'HL_85993.1'
                     Signature: {'cWW-F-F-F-F-F'}
                         NumNT: 7
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: -5.3471
                   OwnSequence: {'AGGCAAUU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 8
            MeanSequenceLength: 8
               DeficitEditData: [4478×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 4478 random sequences, 0 from an alignment, and 1 from 3D structures
Group 212, HL_85993.1  has acceptance rules AlignmentScore >= -25.3471, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.7399
TP   100.00%, TN    95.02%, min    95.02%,   1 3D sequences,     0 alignment sequences, 4478 random sequences,  223 random matches,  7 NTs, cWW-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.02%, Minimum  95.02% using method 6
Number of false positives with core edit > 0 is 223
1 * Deficit + 3 * Core Edit <= 12.3927
Motif index 1


ans = 

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

                       MotifID: 'HL_86012.1'
                     Signature: {'cWW-tWH-F-F-F-F'}
                         NumNT: 8
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 2
                         NumBR: 1
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 22
                      OwnScore: [-3.0954 -3.0954]
                   OwnSequence: {'GUUCGAUCC'  'GUUCGAUCC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9]
            MeanSequenceLength: 9
               DeficitEditData: [3656×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 3656 random sequences, 0 from an alignment, and 2 from 3D structures
Group 213, HL_86012.1  has acceptance rules AlignmentScore >= -23.0954, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  21.9763
TP   100.00%, TN    95.95%, min    95.95%,   2 3D sequences,     0 alignment sequences, 3656 random sequences,  148 random matches,  8 NTs, cWW-tWH-F-F-F-F
Sensitivity 100.00%, Specificity  95.95%, Minimum  95.95% using method 6
Number of false positives with core edit > 0 is 148
1 * Deficit + 3 * Core Edit <= 18.8810
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_86109.1'
                     Signature: {'cWW-F-tWH-F-F-F-F-F-F-F'}
                         NumNT: 12
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 2
                         NumBR: 0
                  NumInstances: 3
                      Truncate: [0×1 double]
                      NumFixed: 38
                      OwnScore: [-6.7310 -6.7310 -9.4336]
                   OwnSequence: {'GGGCGGUGGGAGC'  'GGGCGGUGGGAGC'  'GGAUAGUGAAAGC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [13 13 13]
            MeanSequenceLength: 13
               DeficitEditData: [943×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 943 random sequences, 0 from an alignment, and 3 from 3D structures
Decreased cutoff from  21.1900 because the cutoff seemed overly generous
Group 214, HL_86109.1  has acceptance rules AlignmentScore >= -26.7310, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.7310
TP   100.00%, TN    97.67%, min    97.67%,   3 3D sequences,     0 alignment sequences,  943 random sequences,   22 random matches, 12 NTs, cWW-F-tWH-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  97.67%, Minimum  97.67% 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
Motif index 3


ans = 

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

                       MotifID: 'HL_86769.4'
                     Signature: {'cWW-cWW-cSH-F'}
                         NumNT: 7
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 5
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: [-8.0181 -8.0181 -8.1791 -9.5776 -15.1995]
                   OwnSequence: {'AGGGUCAU'  'AGGGUCAU'  'CACCUCAG'  'GACGAUAU'  'GGCUCAUAACC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8 8 8 11]
            MeanSequenceLength: 8.6000
               DeficitEditData: [8286×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

5 sequences from 3D structures
Using 8286 random sequences, 0 from an alignment, and 5 from 3D structures
Group 215, HL_86769.4  has acceptance rules AlignmentScore >= -28.0181, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  18.9156
TP   100.00%, TN    96.01%, min    96.01%,   5 3D sequences,     0 alignment sequences, 8286 random sequences,  331 random matches,  7 NTs, cWW-cWW-cSH-F
Sensitivity 100.00%, Specificity  96.01%, Minimum  96.01% using method 6
Number of false positives with core edit > 0 is 331
1 * Deficit + 3 * Core Edit <= 10.8975
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: 'HL_86870.2'
                     Signature: {'cWW-F-F-F'}
                         NumNT: 5
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 4
                      Truncate: [0×1 double]
                      NumFixed: 12
                      OwnScore: [-5.3042 -5.3042 -11.3191 -6.5617]
                   OwnSequence: {'GUGUUC'  'GUCUUC'  'ACGCGUGU'  'CAAUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 8 5]
            MeanSequenceLength: 6.2500
               DeficitEditData: [7055×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 7055 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 216, HL_86870.2  has acceptance rules AlignmentScore >= -25.3042, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  14.8042
TP   100.00%, TN    85.49%, min    85.49%,   4 3D sequences,     0 alignment sequences, 7030 random sequences, 1020 random matches,  5 NTs, cWW-F-F-F
Sensitivity 100.00%, Specificity  85.49%, Minimum  85.49% using method 11
Number of false positives with core edit > 0 is 1020
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: 'HL_86883.1'
                     Signature: {'cWW-F-F-F'}
                         NumNT: 5
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 14
                      OwnScore: [-2.4589 -2.4589]
                   OwnSequence: {'GUAUUC'  'GUAUUC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6]
            MeanSequenceLength: 6
               DeficitEditData: [4074×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 4074 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 217, HL_86883.1  has acceptance rules AlignmentScore >= -22.4589, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  11.9589
TP   100.00%, TN    94.79%, min    94.79%,   2 3D sequences,     0 alignment sequences, 4071 random sequences,  212 random matches,  5 NTs, cWW-F-F-F
Sensitivity 100.00%, Specificity  94.79%, Minimum  94.79% using method 11
Number of false positives with core edit > 0 is 212
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: 'HL_87463.1'
                     Signature: {'cWW-cWW-F-F-F-F-F'}
                         NumNT: 9
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 2
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 22
                      OwnScore: -5.6113
                   OwnSequence: {'GUUGGAUAUC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 10
            MeanSequenceLength: 10
               DeficitEditData: [3426×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 3426 random sequences, 0 from an alignment, and 1 from 3D structures
Group 218, HL_87463.1  has acceptance rules AlignmentScore >= -25.6113, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  23.6897
TP   100.00%, TN    95.88%, min    95.88%,   1 3D sequences,     0 alignment sequences, 3426 random sequences,  141 random matches,  9 NTs, cWW-cWW-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.88%, Minimum  95.88% using method 6
Number of false positives with core edit > 0 is 141
1 * Deficit + 3 * Core Edit <= 18.0784
Motif index 1


ans = 

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

                       MotifID: 'HL_87553.1'
                     Signature: {'cWW-F-F-F-F-F'}
                         NumNT: 7
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 7
                      Truncate: [0×1 double]
                      NumFixed: 20
                      OwnScore: [-9.3149 -9.3149 -10.2739 -9.2989 -8.7270 -9.9856 -12.5903]
                   OwnSequence: {'GCGAAAGAC'  'GCGAAAGAC'  'ACUUCGGU'  'CCCACCAG'  'GCGCCAGC'  'UCAUCGA'  'UCUCAUAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9 8 8 8 7 9]
            MeanSequenceLength: 8.2857
               DeficitEditData: [7503×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

7 sequences from 3D structures
Using 7503 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 219, HL_87553.1  has acceptance rules AlignmentScore >= -28.7270, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  18.2270
TP   100.00%, TN    94.81%, min    94.81%,   7 3D sequences,     0 alignment sequences, 7502 random sequences,  389 random matches,  7 NTs, cWW-F-F-F-F-F
Sensitivity 100.00%, Specificity  94.81%, Minimum  94.81% using method 11
Number of false positives with core edit > 0 is 389
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: 'HL_87954.2'
                     Signature: {'cWW-tSW-F'}
                         NumNT: 5
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 5
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 7
                      Truncate: [0×1 double]
                      NumFixed: 12
                      OwnScore: [-5.6698 -6.7684 -5.6698 -7.0406 -7.0078 -7.6549 -6.4970]
                   OwnSequence: {'UGAAAGG'  'UGAAAAG'  'UGAAAGG'  'AGAAAUU'  'GUCCGGC'  'CUUCGCG'  'GUUCGGC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [7 7 7 7 7 7 7]
            MeanSequenceLength: 7
               DeficitEditData: [6419×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

7 sequences from 3D structures
Using 6419 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 220, HL_87954.2  has acceptance rules AlignmentScore >= -25.6698, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.1698
TP   100.00%, TN    93.35%, min    93.35%,   7 3D sequences,     0 alignment sequences, 6388 random sequences,  425 random matches,  5 NTs, cWW-tSW-F
Sensitivity 100.00%, Specificity  93.35%, Minimum  93.35% using method 11
Number of false positives with core edit > 0 is 425
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: 'HL_88205.2'
                     Signature: {'cWW-cWS-tSW-F-F'}
                         NumNT: 7
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 2
                  NumInstances: 7
                      Truncate: [0×1 double]
                      NumFixed: 24
                      OwnScore: [-5.7168 -5.7168 -9.5689 -6.2400 -8.0176 -6.0963 -5.8973]
                   OwnSequence: {'ACGUGCAAAU'  'ACGUGCAAAU'  'UCCUACAAUA'  'GGAUGCAAAC'  'UGCUGAAACA'  'CGUUGAAAAG'  'UGUUGAAAAA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10 10 10 10 10 10]
            MeanSequenceLength: 10
               DeficitEditData: [3584×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

7 sequences from 3D structures
Using 3584 random sequences, 0 from an alignment, and 7 from 3D structures
Group 221, HL_88205.2  has acceptance rules AlignmentScore >= -25.7168, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  20.7279
TP   100.00%, TN    96.01%, min    96.01%,   7 3D sequences,     0 alignment sequences, 3583 random sequences,  143 random matches,  7 NTs, cWW-cWS-tSW-F-F
Sensitivity 100.00%, Specificity  96.01%, Minimum  96.01% using method 6
Number of false positives with core edit > 0 is 143
1 * Deficit + 3 * Core Edit <= 15.0111
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: 'HL_88364.2'
                     Signature: {'cWW-cWW-F-F-F-F-F-F-F-F-F-F-F'}
                         NumNT: 15
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 12
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 3
                      Truncate: [0×1 double]
                      NumFixed: 36
                      OwnScore: [-10.2607 -10.2607 -11.7850]
                   OwnSequence: {'UACUUAUUUCCUUUGA'  'UACUUAUUUCCUUUGA'  'AUUUUGUUGGUUUCU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [16 16 15]
            MeanSequenceLength: 15.6667
               DeficitEditData: [61×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 61 random sequences, 0 from an alignment, and 3 from 3D structures
Group 222, HL_88364.2  has acceptance rules AlignmentScore >= -30.2607, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  30.0850
TP   100.00%, TN    96.72%, min    96.72%,   3 3D sequences,     0 alignment sequences,   61 random sequences,    2 random matches, 15 NTs, cWW-cWW-F-F-F-F-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.72%, Minimum  96.72% using method 6
Number of false positives with core edit > 0 is 2
1 * Deficit + 3 * Core Edit <= 19.8243
Motif index 1
Motif index 2
Motif index 3


ans = 

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

                       MotifID: 'HL_88558.1'
                     Signature: {'cWW-tSH-F-F-F-F-F-F-F'}
                         NumNT: 11
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 26
                      OwnScore: -8.6616
                   OwnSequence: {'CGAAUCCAUAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 12
            MeanSequenceLength: 12
               DeficitEditData: [1634×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 1634 random sequences, 0 from an alignment, and 1 from 3D structures
Group 223, HL_88558.1  has acceptance rules AlignmentScore >= -28.6616, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.3553
TP   100.00%, TN    95.84%, min    95.84%,   1 3D sequences,     0 alignment sequences, 1634 random sequences,   68 random matches, 11 NTs, cWW-tSH-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.84%, Minimum  95.84% using method 6
Number of false positives with core edit > 0 is 68
1 * Deficit + 3 * Core Edit <= 17.6937
Motif index 1


ans = 

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

                       MotifID: 'HL_89199.2'
                     Signature: {'cWW-F-F-F'}
                         NumNT: 5
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 5
                      Truncate: [0×1 double]
                      NumFixed: 14
                      OwnScore: [-2.3710 -2.3710 -2.3710 -2.3710 -2.3710]
                   OwnSequence: {'CUGAUG'  'CUGAUG'  'CUGAUG'  'CUGAUG'  'CUGAUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 6 6 6]
            MeanSequenceLength: 6
               DeficitEditData: [3775×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

5 sequences from 3D structures
Using 3775 random sequences, 0 from an alignment, and 5 from 3D structures
Group 224, HL_89199.2  has acceptance rules AlignmentScore >= -22.3710, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  13.1667
TP   100.00%, TN    95.67%, min    95.67%,   5 3D sequences,     0 alignment sequences, 3768 random sequences,  163 random matches,  5 NTs, cWW-F-F-F
Sensitivity 100.00%, Specificity  95.67%, Minimum  95.67% using method 6
Number of false positives with core edit > 0 is 163
1 * Deficit + 3 * Core Edit <= 10.7958
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: 'HL_89346.1'
                     Signature: {'cWW-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F'}
                         NumNT: 17
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 16
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 46
                      OwnScore: [-20.6578 -17.8309]
                   OwnSequence: {'AGAAGGGGGCAACUCCAUCU'  'CUUCCCGAAUUGUGGAUAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [20 19]
            MeanSequenceLength: 19.5000
               DeficitEditData: [2×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 2 random sequences, 0 from an alignment, and 2 from 3D structures
Group 225, HL_89346.1  has acceptance rules AlignmentScore >= -37.8309, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  42.8309
TP   100.00%, TN    50.00%, min    50.00%,   2 3D sequences,     0 alignment sequences,    2 random sequences,    1 random matches, 17 NTs, cWW-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F
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
Motif index 2


ans = 

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

                       MotifID: 'HL_89567.2'
                     Signature: {'cWW-F-F-F'}
                         NumNT: 5
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 4
                        NumBPh: 1
                         NumBR: 1
                  NumInstances: 8
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: [-3.9163 -3.9163 -3.9163 -3.9163 -3.9163 -5.6087 -5.6087 -8.9880]
                   OwnSequence: {'CGACACAG'  'CGACACAG'  'CGACACAG'  'CGACACAG'  'CGACACAG'  'CGCAGCAG'  'CGCAGCAG'  'AGGCAAUU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8 8 8 8 8 8 8]
            MeanSequenceLength: 8
               DeficitEditData: [5787×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

8 sequences from 3D structures
Using 5787 random sequences, 0 from an alignment, and 8 from 3D structures
Group 226, HL_89567.2  has acceptance rules AlignmentScore >= -23.9163, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.4726
TP   100.00%, TN    95.97%, min    95.97%,   8 3D sequences,     0 alignment sequences, 5787 random sequences,  233 random matches,  5 NTs, cWW-F-F-F
Sensitivity 100.00%, Specificity  95.97%, Minimum  95.97% using method 6
Number of false positives with core edit > 0 is 233
1 * Deficit + 3 * Core Edit <= 12.5563
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: 'HL_89881.5'
                     Signature: {'cWW-tHW-F-F-F-F-F-F'}
                         NumNT: 10
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 4
                      Truncate: [0×1 double]
                      NumFixed: 24
                      OwnScore: [-4.8200 -5.6673 -5.1411 -5.1411]
                   OwnSequence: {'UUUGAUCCUGG'  'UUUGAUCAUGG'  'GUUGAUCCUGC'  'GUUGAUCCUGC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11 11 11]
            MeanSequenceLength: 11
               DeficitEditData: [1654×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 1654 random sequences, 0 from an alignment, and 4 from 3D structures
Decreased cutoff from  21.6251 because the cutoff seemed overly generous
Group 227, HL_89881.5  has acceptance rules AlignmentScore >= -24.8200, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.8200
TP   100.00%, TN    97.88%, min    97.88%,   4 3D sequences,     0 alignment sequences, 1654 random sequences,   35 random matches, 10 NTs, cWW-tHW-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  97.88%, Minimum  97.88% using method 8
Number of false positives with core edit > 0 is 35
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: 'HL_89893.1'
                     Signature: {'cWW-F-F-F-F'}
                         NumNT: 6
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: -4.6417
                   OwnSequence: {'CAGAGCG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 7
            MeanSequenceLength: 7
               DeficitEditData: [6334×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 6334 random sequences, 0 from an alignment, and 1 from 3D structures
Group 228, HL_89893.1  has acceptance rules AlignmentScore >= -24.6417, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.9375
TP   100.00%, TN    95.80%, min    95.80%,   1 3D sequences,     0 alignment sequences, 6334 random sequences,  266 random matches,  6 NTs, cWW-F-F-F-F
Sensitivity 100.00%, Specificity  95.80%, Minimum  95.80% using method 6
Number of false positives with core edit > 0 is 266
1 * Deficit + 3 * Core Edit <= 12.2958
Motif index 1


ans = 

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

                       MotifID: 'HL_90620.1'
                     Signature: {'cWW-F-F-F-F-cSW-cSH-F'}
                         NumNT: 11
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 24
                      OwnScore: [-7.0475 -7.0475]
                   OwnSequence: {'AACCGUAAAAU'  'AACCGUAAAAU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11]
            MeanSequenceLength: 11
               DeficitEditData: [1873×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 1873 random sequences, 0 from an alignment, and 2 from 3D structures
Group 229, HL_90620.1  has acceptance rules AlignmentScore >= -27.0475, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.3509
TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences, 1873 random sequences,   75 random matches, 11 NTs, cWW-F-F-F-F-cSW-cSH-F
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 75
1 * Deficit + 3 * Core Edit <= 17.3034
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_91503.7'
                     Signature: {'cWW-F-F-F-F-F-F-F'}
                         NumNT: 9
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 3
                      Truncate: [0×1 double]
                      NumFixed: 26
                      OwnScore: [-6.9866 -6.9866 -8.0651]
                   OwnSequence: {'GUUCGUGGAGC'  'GUUCGUGAAAC'  'ACACGUGGUAU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11 11]
            MeanSequenceLength: 11
               DeficitEditData: [2935×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 2935 random sequences, 0 from an alignment, and 3 from 3D structures
Group 230, HL_91503.7  has acceptance rules AlignmentScore >= -26.9866, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.9955
TP   100.00%, TN    96.01%, min    96.01%,   3 3D sequences,     0 alignment sequences, 2935 random sequences,  117 random matches,  9 NTs, cWW-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.01%, Minimum  96.01% using method 6
Number of false positives with core edit > 0 is 117
1 * Deficit + 3 * Core Edit <= 18.0089
Motif index 1
Motif index 2
Motif index 3


ans = 

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

                       MotifID: 'HL_91641.1'
                     Signature: {'cWW-F-F-F-F-F-F-F-F-cSW-F-F-F-F'}
                         NumNT: 16
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 13
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 46
                      OwnScore: -12.7400
                   OwnSequence: {'AGUCGCGUGAUAAAUGU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 17
            MeanSequenceLength: 17
               DeficitEditData: [46×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 46 random sequences, 0 from an alignment, and 1 from 3D structures
Group 231, HL_91641.1  has acceptance rules AlignmentScore >= -32.7400, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  29.8388
TP   100.00%, TN    95.65%, min    95.65%,   1 3D sequences,     0 alignment sequences,   46 random sequences,    2 random matches, 16 NTs, cWW-F-F-F-F-F-F-F-F-cSW-F-F-F-F
Sensitivity 100.00%, Specificity  95.65%, Minimum  95.65% using method 6
Number of false positives with core edit > 0 is 2
1 * Deficit + 3 * Core Edit <= 17.0988
Motif index 1


ans = 

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

                       MotifID: 'HL_91939.2'
                     Signature: {'cWW-tSH-tHH-tWW-F-F-F'}
                         NumNT: 11
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 8
                      Truncate: [0×1 double]
                      NumFixed: 20
                      OwnScore: [-8.0697 -9.9568 -8.0697 -8.5479 -8.4601 -8.4601 -9.8525 -15.8402]
                   OwnSequence: {1×8 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [13 13 13 13 13 13 13 11]
            MeanSequenceLength: 12.7500
               DeficitEditData: [2749×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

8 sequences from 3D structures
Using 2749 random sequences, 0 from an alignment, and 8 from 3D structures
Group 232, HL_91939.2  has acceptance rules AlignmentScore >= -28.0697, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  27.4612
TP   100.00%, TN    96.00%, min    96.00%,   8 3D sequences,     0 alignment sequences, 2749 random sequences,  110 random matches, 11 NTs, cWW-tSH-tHH-tWW-F-F-F
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 110
1 * Deficit + 3 * Core Edit <= 19.3915
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: 'HL_92488.1'
                     Signature: {'cWW-cWW-F-cSS-F-F-F-F-F-F'}
                         NumNT: 13
                  NumBasepairs: 4
                    Structured: 1
                     NumStacks: 9
                        NumBPh: 0
                         NumBR: 2
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 36
                      OwnScore: -12.2192
                   OwnSequence: {'GAAACCGCCGAUAUGC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 16
            MeanSequenceLength: 16
               DeficitEditData: [28×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 28 random sequences, 0 from an alignment, and 1 from 3D structures
Group 233, HL_92488.1  has acceptance rules AlignmentScore >= -32.2192, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  31.6199
TP   100.00%, TN    96.43%, min    96.43%,   1 3D sequences,     0 alignment sequences,   28 random sequences,    1 random matches, 13 NTs, cWW-cWW-F-cSS-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.43%, Minimum  96.43% using method 6
Number of false positives with core edit > 0 is 1
1 * Deficit + 3 * Core Edit <= 19.4007
Motif index 1


ans = 

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

                       MotifID: 'HL_93135.1'
                     Signature: {'cWW-F-F-F-F-F-F'}
                         NumNT: 8
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 22
                      OwnScore: -8.5290
                   OwnSequence: {'CUAUGGCUAUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 11
            MeanSequenceLength: 11
               DeficitEditData: [1896×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 1896 random sequences, 0 from an alignment, and 1 from 3D structures
Group 234, HL_93135.1  has acceptance rules AlignmentScore >= -28.5290, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.9980
TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences, 1896 random sequences,   76 random matches,  8 NTs, cWW-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 76
1 * Deficit + 3 * Core Edit <= 16.4689
Motif index 1


ans = 

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

                       MotifID: 'HL_93324.4'
                     Signature: {'cWW-F-F-F-F-F-F'}
                         NumNT: 8
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 24
                      Truncate: [0×1 double]
                      NumFixed: 22
                      OwnScore: [-10.6554 -9.7351 -10.5330 -8.6365 -7.3880 -11.2146 -8.3938 -8.3865 -9.7111 -8.3938 -9.2144 -9.7111 … ]
                   OwnSequence: {1×24 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 8 8 8 8 8 8 8 8 8 8 8 8 8 9 9 9 9 9 9 9 9 9 10]
            MeanSequenceLength: 8.4583
               DeficitEditData: [6077×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

24 sequences from 3D structures
Using 6077 random sequences, 0 from an alignment, and 24 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 235, HL_93324.4  has acceptance rules AlignmentScore >= -27.3880, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  16.8880
TP   100.00%, TN    93.51%, min    93.51%,  24 3D sequences,     0 alignment sequences, 6067 random sequences,  394 random matches,  8 NTs, cWW-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  93.51%, Minimum  93.51% using method 11
Number of false positives with core edit > 0 is 394
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


ans = 

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

                       MotifID: 'HL_93383.1'
                     Signature: {'cWW-cSH-F-F-F-F-F-F'}
                         NumNT: 9
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 28
                      OwnScore: [-3.4763 -3.4763]
                   OwnSequence: {'GCCCUAAGC'  'GCUCAAAGC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [9 9]
            MeanSequenceLength: 9
               DeficitEditData: [1255×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 1255 random sequences, 0 from an alignment, and 2 from 3D structures
Group 236, HL_93383.1  has acceptance rules AlignmentScore >= -23.4763, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  21.3996
TP   100.00%, TN    96.02%, min    96.02%,   2 3D sequences,     0 alignment sequences, 1255 random sequences,   50 random matches,  9 NTs, cWW-cSH-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.02%, Minimum  96.02% using method 6
Number of false positives with core edit > 0 is 50
1 * Deficit + 3 * Core Edit <= 17.9232
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_93438.2'
                     Signature: {'cWW-F-F-F-F-F-F-F-F'}
                         NumNT: 10
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 6
                      Truncate: [0×1 double]
                      NumFixed: 32
                      OwnScore: [-8.9856 -7.7548 -9.8228 -7.2885 -8.2947 -8.2947]
                   OwnSequence: {'CGAUUACCUG'  'UGCCAAGCUG'  'UUACUAACGA'  'UGGCUACCUG'  'CAGCGAAAUG'  'CAGCGAAAUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10 10 10 10 10]
            MeanSequenceLength: 10
               DeficitEditData: [5735×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

6 sequences from 3D structures
Using 5735 random sequences, 0 from an alignment, and 6 from 3D structures
Group 237, HL_93438.2  has acceptance rules AlignmentScore >= -27.2885, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  23.9053
TP   100.00%, TN    96.01%, min    96.01%,   6 3D sequences,     0 alignment sequences, 5735 random sequences,  229 random matches, 10 NTs, cWW-F-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.01%, Minimum  96.01% using method 6
Number of false positives with core edit > 0 is 229
1 * Deficit + 3 * Core Edit <= 16.6169
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: 'HL_93535.1'
                     Signature: {'cWW-F-F-F-F'}
                         NumNT: 6
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 6
                      Truncate: [0×1 double]
                      NumFixed: 20
                      OwnScore: [-6.2617 -6.2617 -7.6421 -7.5157 -6.0995 -7.8154]
                   OwnSequence: {'CAGCCG'  'CAGCCG'  'UGAUAAA'  'CGAACAG'  'CGUAAG'  'UAAGGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [6 6 7 7 6 6]
            MeanSequenceLength: 6.3333
               DeficitEditData: [6698×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

6 sequences from 3D structures
Using 6698 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 238, HL_93535.1  has acceptance rules AlignmentScore >= -26.0995, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  15.5995
TP   100.00%, TN    85.65%, min    85.65%,   6 3D sequences,     0 alignment sequences, 6681 random sequences,  959 random matches,  6 NTs, cWW-F-F-F-F
Sensitivity 100.00%, Specificity  85.65%, Minimum  85.65% using method 11
Number of false positives with core edit > 0 is 959
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: 'HL_93616.2'
                     Signature: {'cWW-cWS-F-F-F-F'}
                         NumNT: 8
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 8
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: [-7.3493 -5.8830 -5.8830 -5.8830 -5.8830 -5.8830 -14.9897 -5.8830]
                   OwnSequence: {1×8 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11 11 11 11 11 12 11]
            MeanSequenceLength: 11.1250
               DeficitEditData: [927×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

8 sequences from 3D structures
Using 927 random sequences, 0 from an alignment, and 8 from 3D structures
Decreased cutoff from  21.1935 because the cutoff seemed overly generous
Group 239, HL_93616.2  has acceptance rules AlignmentScore >= -25.8830, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.8830
TP   100.00%, TN    97.52%, min    97.52%,   8 3D sequences,     0 alignment sequences,  927 random sequences,   23 random matches,  8 NTs, cWW-cWS-F-F-F-F
Sensitivity 100.00%, Specificity  97.52%, Minimum  97.52% using method 8
Number of false positives with core edit > 0 is 23
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


ans = 

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

                       MotifID: 'HL_94376.1'
                     Signature: {'cWW-F-F-F-F-F-F-F-F-F'}
                         NumNT: 11
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 3
                      Truncate: [0×1 double]
                      NumFixed: 28
                      OwnScore: [-7.7719 -7.7719 -12.9427]
                   OwnSequence: {'GAAGUGCACAC'  'GAAGUGCACAC'  'UAGUCUCUUUCG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11 12]
            MeanSequenceLength: 11.3333
               DeficitEditData: [1629×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 1629 random sequences, 0 from an alignment, and 3 from 3D structures
Group 240, HL_94376.1  has acceptance rules AlignmentScore >= -27.7719, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  25.9328
TP   100.00%, TN    96.01%, min    96.01%,   3 3D sequences,     0 alignment sequences, 1629 random sequences,   65 random matches, 11 NTs, cWW-F-F-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  96.01%, Minimum  96.01% using method 6
Number of false positives with core edit > 0 is 65
1 * Deficit + 3 * Core Edit <= 18.1608
Motif index 1
Motif index 2
Motif index 3


ans = 

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

                       MotifID: 'HL_94980.1'
                     Signature: {'cWW-F-F'}
                         NumNT: 4
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 1
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 12
                      OwnScore: -2.9167
                   OwnSequence: {'CUUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 4
            MeanSequenceLength: 4
               DeficitEditData: [3515×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 3515 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 241, HL_94980.1  has acceptance rules AlignmentScore >= -22.9167, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  12.4167
TP   100.00%, TN    70.87%, min    70.87%,   1 3D sequences,     0 alignment sequences, 3406 random sequences,  992 random matches,  4 NTs, cWW-F-F
Sensitivity 100.00%, Specificity  70.87%, Minimum  70.87% using method 11
Number of false positives with core edit > 0 is 992
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: 'HL_97733.1'
                     Signature: {'cWW-F-F-F-cSH-F'}
                         NumNT: 8
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 20
                      OwnScore: -8.0884
                   OwnSequence: {'CCCGGUCAGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 10
            MeanSequenceLength: 10
               DeficitEditData: [2527×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 2527 random sequences, 0 from an alignment, and 1 from 3D structures
Group 242, HL_97733.1  has acceptance rules AlignmentScore >= -28.0884, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.5623
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 2527 random sequences,  101 random matches,  8 NTs, cWW-F-F-F-cSH-F
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 101
1 * Deficit + 3 * Core Edit <= 16.4738
Motif index 1


ans = 

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

                       MotifID: 'HL_97756.2'
                     Signature: {'cWW-cSH-cWS-F-tSW-cSW-F-cWW-F-F-F'}
                         NumNT: 14
                  NumBasepairs: 6
                    Structured: 1
                     NumStacks: 12
                        NumBPh: 2
                         NumBR: 4
                  NumInstances: 6
                      Truncate: [0×1 double]
                      NumFixed: 34
                      OwnScore: [-6.7251 -6.2143 -4.7790 -5.1157 -4.7790 -4.7790]
                   OwnSequence: {1×6 cell}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [15 15 15 15 15 15]
            MeanSequenceLength: 15
               DeficitEditData: [19×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

6 sequences from 3D structures
Using 19 random sequences, 0 from an alignment, and 6 from 3D structures
Group 243, HL_97756.2  has acceptance rules AlignmentScore >= -24.7790, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  29.7790
TP   100.00%, TN   100.00%, min   100.00%,   6 3D sequences,     0 alignment sequences,   19 random sequences,    0 random matches, 14 NTs, cWW-cSH-cWS-F-tSW-cSW-F-cWW-F-F-F
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
Motif index 5
Motif index 6


ans = 

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

                       MotifID: 'HL_97917.2'
                     Signature: {'cWW-F-F-F-F'}
                         NumNT: 6
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 3
                      Truncate: [0×1 double]
                      NumFixed: 18
                      OwnScore: [-8.5302 -9.5810 -8.3964]
                   OwnSequence: {'CUUCAACG'  'GGAGGAC'  'UUUUUUAAUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [8 7 10]
            MeanSequenceLength: 8.3333
               DeficitEditData: [8117×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

3 sequences from 3D structures
Using 8117 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 244, HL_97917.2  has acceptance rules AlignmentScore >= -28.3964, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  17.8964
TP   100.00%, TN    92.79%, min    92.79%,   3 3D sequences,     0 alignment sequences, 8116 random sequences,  585 random matches,  6 NTs, cWW-F-F-F-F
Sensitivity 100.00%, Specificity  92.79%, Minimum  92.79% using method 11
Number of false positives with core edit > 0 is 585
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: 'HL_97983.1'
                     Signature: {'cWW-F-F'}
                         NumNT: 4
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 0
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 12
                      OwnScore: -8.1869
                   OwnSequence: {'AGGGAUUUU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 9
            MeanSequenceLength: 9
               DeficitEditData: [2424×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 2424 random sequences, 0 from an alignment, and 1 from 3D structures
Group 245, HL_97983.1  has acceptance rules AlignmentScore >= -28.1869, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  19.6617
TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences, 2423 random sequences,   97 random matches,  4 NTs, cWW-F-F
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 97
1 * Deficit + 3 * Core Edit <= 11.4748
Motif index 1


ans = 

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

                       MotifID: 'HL_98252.1'
                     Signature: {'cWW-tWW-F-F-F-F'}
                         NumNT: 8
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 7
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 20
                      OwnScore: -7.2938
                   OwnSequence: {'AUUAUUUAUUU'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 11
            MeanSequenceLength: 11
               DeficitEditData: [1704×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 1704 random sequences, 0 from an alignment, and 1 from 3D structures
Group 246, HL_98252.1  has acceptance rules AlignmentScore >= -27.2938, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  23.7722
TP   100.00%, TN    95.95%, min    95.95%,   1 3D sequences,     0 alignment sequences, 1704 random sequences,   69 random matches,  8 NTs, cWW-tWW-F-F-F-F
Sensitivity 100.00%, Specificity  95.95%, Minimum  95.95% using method 6
Number of false positives with core edit > 0 is 69
1 * Deficit + 3 * Core Edit <= 16.4785
Motif index 1


ans = 

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

                       MotifID: 'HL_98864.1'
                     Signature: {'cWW-tWH-F-F-F-F-F-F'}
                         NumNT: 10
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 1
                         NumBR: 0
                  NumInstances: 4
                      Truncate: [0×1 double]
                      NumFixed: 26
                      OwnScore: [-4.6293 -5.1401 -4.6293 -8.5293]
                   OwnSequence: {'GUCCCAAGCC'  'GUCCUAAGCC'  'GUCCCAAGCC'  'GUAGGUAGUC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10 10 10]
            MeanSequenceLength: 10
               DeficitEditData: [3513×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

4 sequences from 3D structures
Using 3513 random sequences, 0 from an alignment, and 4 from 3D structures
Group 247, HL_98864.1  has acceptance rules AlignmentScore >= -24.6293, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  24.5677
TP   100.00%, TN    95.99%, min    95.99%,   4 3D sequences,     0 alignment sequences, 3513 random sequences,  141 random matches, 10 NTs, cWW-tWH-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.99%, Minimum  95.99% using method 6
Number of false positives with core edit > 0 is 141
1 * Deficit + 3 * Core Edit <= 19.9385
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: 'HL_98870.1'
                     Signature: {'cWW-tSH-tWW-F-F-F-F-F'}
                         NumNT: 11
                  NumBasepairs: 3
                    Structured: 1
                     NumStacks: 12
                        NumBPh: 2
                         NumBR: 2
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 28
                      OwnScore: [-13.4219 -9.2985]
                   OwnSequence: {'CGUAGGCUACAGAGAAG'  'UGUGGUACAGAGAAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [17 15]
            MeanSequenceLength: 16
               DeficitEditData: [221×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 221 random sequences, 0 from an alignment, and 2 from 3D structures
Decreased cutoff from  21.1548 because the cutoff seemed overly generous
Group 248, HL_98870.1  has acceptance rules AlignmentScore >= -29.2985, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  29.4620
TP   100.00%, TN    98.19%, min    98.19%,   2 3D sequences,     0 alignment sequences,  221 random sequences,    4 random matches, 11 NTs, cWW-tSH-tWW-F-F-F-F-F
Sensitivity 100.00%, Specificity  98.19%, Minimum  98.19% using method 8
Number of false positives with core edit > 0 is 4
1 * Deficit + 3 * Core Edit <= 20.1634
Motif index 1
Motif index 2


ans = 

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

                       MotifID: 'HL_99040.1'
                     Signature: {'F-F-F-F-F-F'}
                         NumNT: 6
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 1
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 16
                      OwnScore: -3.2183
                   OwnSequence: {'UUGCGG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 6
            MeanSequenceLength: 6
               DeficitEditData: [3943×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 3943 random sequences, 0 from an alignment, and 1 from 3D structures
Group 249, HL_99040.1  has acceptance rules AlignmentScore >= -23.2183, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  14.5843
TP   100.00%, TN    95.96%, min    95.96%,   1 3D sequences,     0 alignment sequences, 3938 random sequences,  159 random matches,  6 NTs, F-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.96%, Minimum  95.96% using method 6
Number of false positives with core edit > 0 is 159
1 * Deficit + 3 * Core Edit <= 11.3660
Motif index 1


ans = 

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

                       MotifID: 'HL_99324.1'
                     Signature: {'cWW-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F'}
                         NumNT: 17
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 17
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 2
                      Truncate: [0×1 double]
                      NumFixed: 36
                      OwnScore: [-12.8649 -13.9415]
                   OwnSequence: {'CAACUUAGGAUUUUAGG'  'UAUUUUGUUGGUUUCUA'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [17 17]
            MeanSequenceLength: 17
               DeficitEditData: [11×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

2 sequences from 3D structures
Using 11 random sequences, 0 from an alignment, and 2 from 3D structures
Group 250, HL_99324.1  has acceptance rules AlignmentScore >= -32.8649, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  37.8649
TP   100.00%, TN    90.91%, min    90.91%,   2 3D sequences,     0 alignment sequences,   11 random sequences,    1 random matches, 17 NTs, cWW-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F
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
Motif index 2


ans = 

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

                       MotifID: 'HL_99748.1'
                     Signature: {'cWW-F-F-cSH'}
                         NumNT: 6
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 3
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 1
                      Truncate: [0×1 double]
                      NumFixed: 16
                      OwnScore: -6.7021
                   OwnSequence: {'CCAGUUAG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: 8
            MeanSequenceLength: 8
               DeficitEditData: [6578×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

1 sequences from 3D structures
Using 6578 random sequences, 0 from an alignment, and 1 from 3D structures
Group 251, HL_99748.1  has acceptance rules AlignmentScore >= -26.7021, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  19.3432
TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences, 6578 random sequences,  264 random matches,  6 NTs, cWW-F-F-cSH
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 <= 12.6411
Motif index 1


ans = 

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

                       MotifID: 'HL_99769.3'
                     Signature: {'cWW-cWW-F-F-F-F'}
                         NumNT: 8
                  NumBasepairs: 2
                    Structured: 1
                     NumStacks: 6
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 6
                      Truncate: [0×1 double]
                      NumFixed: 20
                      OwnScore: [-8.7695 -8.7695 -11.6250 -14.9996 -14.1570 -12.9200]
                   OwnSequence: {'GUAGUGGUAUC'  'GUAGUGGUAUC'  'GUAGUGGUAAUC'  'CCCGAAUUGUGG'  'AACGCUUGCGUU'  'CAAGCUUGCUUG'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [11 11 12 12 12 12]
            MeanSequenceLength: 11.6667
               DeficitEditData: [3126×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

6 sequences from 3D structures
Using 3126 random sequences, 0 from an alignment, and 6 from 3D structures
Group 252, HL_99769.3  has acceptance rules AlignmentScore >= -28.7695, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  26.9949
TP   100.00%, TN    96.00%, min    96.00%,   6 3D sequences,     0 alignment sequences, 3126 random sequences,  125 random matches,  8 NTs, cWW-cWW-F-F-F-F
Sensitivity 100.00%, Specificity  96.00%, Minimum  96.00% using method 6
Number of false positives with core edit > 0 is 125
1 * Deficit + 3 * Core Edit <= 18.2254
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: 'HL_99867.1'
                     Signature: {'cWW-F-F-F-F-F-F-F-F'}
                         NumNT: 10
                  NumBasepairs: 1
                    Structured: 1
                     NumStacks: 8
                        NumBPh: 0
                         NumBR: 0
                  NumInstances: 5
                      Truncate: [0×1 double]
                      NumFixed: 24
                      OwnScore: [-10.5334 -9.4348 -9.5838 -9.0983 -8.5875]
                   OwnSequence: {'GAAGUGCAAC'  'GAUGCUUGUC'  'AUUAGGUAGU'  'GCUGGCGGUC'  'GUUCGGGGAC'}
                  DeficitCoeff: 1
                 CoreEditCoeff: 3
               SequenceLengths: [10 10 10 10 10]
            MeanSequenceLength: 10
               DeficitEditData: [3227×2 double]
              RandomQuantile80: []
              RandomQuantile96: []
              RandomQuantile98: []
                  CutoffMethod: []
              TruePositiveRate: []
              TrueNegativeRate: []
           NumberOf3DSequences: []
    NumberOfAlignmentSequences: []
       NumberOfRandomSequences: []
        NumberOfFalsePositives: []
                 DeficitCutoff: []
                CoreEditCutoff: []
             DeficitEditCutoff: []
                      MinScore: []
                      MaxScore: []
               ScoreEditCutoff: []

5 sequences from 3D structures
Using 3227 random sequences, 0 from an alignment, and 5 from 3D structures
Group 253, HL_99867.1  has acceptance rules AlignmentScore >= -28.5875, CoreEdit <= 5, and   3.0000 * CoreEdit -   1.0000 * AlignmentScore <=  22.7774
TP   100.00%, TN    95.94%, min    95.94%,   5 3D sequences,     0 alignment sequences, 3227 random sequences,  131 random matches, 10 NTs, cWW-F-F-F-F-F-F-F-F
Sensitivity 100.00%, Specificity  95.94%, Minimum  95.94% using method 6
Number of false positives with core edit > 0 is 131
1 * Deficit + 3 * Core Edit <= 14.1900
Motif index 1
Motif index 2
Motif index 3
Motif index 4
Motif index 5

 10 (  3.95%) 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
156 ( 61.66%) models had cutoff set from random sequences only
  0 (  0.00%) random cutoff models had their cutoff made more generous
 21 (  8.30%) 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
 60 ( 23.72%) models got the minimum cutoff
253 groups, total in this table is 253
Group   1, HL_00317.1  has acceptance rules -15.1580 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-15.1580 - AlignmentScore) +   3.0000 * CoreEdit <=  25.0000, method  1,TP   100.00%, TN    80.00%, min    80.00%,   1 3D sequences,     0 alignment sequences,     5 random sequences,    1 random matches, 19 NTs, cWW-F-cSS-F-F-F-F-F-F-F-F-F-F-F-F-F-F
Group   2, HL_00914.1  has acceptance rules  -5.4881 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.4881 - AlignmentScore) +   3.0000 * CoreEdit <=  11.1972, method  6,TP   100.00%, TN    95.84%, min    95.84%,   1 3D sequences,     0 alignment sequences,  5984 random sequences,  249 random matches,  6 NTs, cWW-F-F-F-F
Group   3, HL_01255.1  has acceptance rules  -8.3341 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.3341 - AlignmentScore) +   3.0000 * CoreEdit <=  17.8216, method  6,TP   100.00%, TN    95.94%, min    95.94%,   1 3D sequences,     0 alignment sequences,  1452 random sequences,   59 random matches,  8 NTs, F-F-F-F-F-F-F-F
Group   4, HL_01609.3  has acceptance rules  -4.7594 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.7594 - AlignmentScore) +   3.0000 * CoreEdit <=  12.5144, method  6,TP   100.00%, TN    96.00%, min    96.00%,  18 3D sequences,     0 alignment sequences,  5875 random sequences,  235 random matches,  7 NTs, cWW-tWH-F-F-F
Group   5, HL_01962.2  has acceptance rules  -6.6529 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.6529 - AlignmentScore) +   3.0000 * CoreEdit <=  16.8691, method  6,TP   100.00%, TN    95.99%, min    95.99%,   6 3D sequences,     0 alignment sequences,  3391 random sequences,  136 random matches,  7 NTs, cWW-tWH-tWH-F
Group   6, HL_02483.1  has acceptance rules  -7.7782 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.7782 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    96.31%, min    96.31%,   1 3D sequences,     0 alignment sequences,  1680 random sequences,   62 random matches, 10 NTs, cWW-tWH-F-cSH-F-F-F
Group   7, HL_02581.1  has acceptance rules  -9.5274 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.5274 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0469, method  8,TP   100.00%, TN    98.32%, min    98.32%,   2 3D sequences,     0 alignment sequences,   119 random sequences,    2 random matches, 11 NTs, cWW-tSH-cWS-tSW-F-F-F
Group   8, HL_02817.2  has acceptance rules  -4.7906 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.7906 - AlignmentScore) +   3.0000 * CoreEdit <=  11.9680, method  6,TP   100.00%, TN    95.99%, min    95.99%,   3 3D sequences,     0 alignment sequences,  5640 random sequences,  226 random matches,  6 NTs, cWW-F-F-F-F
Group   9, HL_02887.3  has acceptance rules  -5.3391 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.3391 - AlignmentScore) +   3.0000 * CoreEdit <=  19.6950, method  6,TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences,  3123 random sequences,  125 random matches, 10 NTs, cWW-tWH-F-F-F-F-F-F
Group  10, HL_04171.7  has acceptance rules  -5.2298 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.2298 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.78%, min    97.78%,   9 3D sequences,     0 alignment sequences,  2835 random sequences,   63 random matches, 10 NTs, cWW-cWW-F-F-F-F-F-F
Group  11, HL_04259.3  has acceptance rules  -6.5743 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.5743 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    95.72%, min    95.72%,   7 3D sequences,     0 alignment sequences,  6805 random sequences,  291 random matches,  8 NTs, cWW-F-F-F-F-F-F
Group  12, HL_04641.1  has acceptance rules  -6.4541 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.4541 - AlignmentScore) +   3.0000 * CoreEdit <=  16.0244, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences,  3522 random sequences,  141 random matches,  7 NTs, cWW-F-F-F-F-F
Group  13, HL_04642.1  has acceptance rules  -7.8711 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.8711 - AlignmentScore) +   3.0000 * CoreEdit <=  17.9355, method  6,TP   100.00%, TN    96.00%, min    96.00%,   3 3D sequences,     0 alignment sequences,  3497 random sequences,  140 random matches,  7 NTs, cWW-F-F-F-F-F
Group  14, HL_04725.1  has acceptance rules  -5.0288 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.0288 - AlignmentScore) +   3.0000 * CoreEdit <=  20.2255, method  8,TP   100.00%, TN    97.96%, min    97.96%,   2 3D sequences,     0 alignment sequences,   783 random sequences,   16 random matches,  8 NTs, cWW-cWS-cWW-cWW-cWS
Group  15, HL_04783.2  has acceptance rules  -6.0967 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.0967 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    81.03%, min    81.03%,   9 3D sequences,     0 alignment sequences,  7734 random sequences, 1467 random matches,  5 NTs, cWW-F-F-F
Group  16, HL_05304.3  has acceptance rules -10.4004 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-10.4004 - AlignmentScore) +   3.0000 * CoreEdit <=  19.3222, method  6,TP   100.00%, TN    96.02%, min    96.02%,   5 3D sequences,     0 alignment sequences,  1534 random sequences,   61 random matches, 13 NTs, cWW-cWW-F-F-tSH-F-F-F-F-F
Group  17, HL_06059.6  has acceptance rules  -4.7484 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.7484 - AlignmentScore) +   3.0000 * CoreEdit <=  13.3125, method  6,TP    98.04%, TN    96.01%, min    96.01%,  51 3D sequences,     0 alignment sequences,  3186 random sequences,  127 random matches,  9 NTs, cWW-F-F-F-F-F-F-F
Group  18, HL_06226.4  has acceptance rules  -8.0798 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.0798 - AlignmentScore) +   3.0000 * CoreEdit <=  19.7766, method  6,TP   100.00%, TN    96.00%, min    96.00%,   4 3D sequences,     0 alignment sequences,  2877 random sequences,  115 random matches,  9 NTs, cWW-F-F-F-F-F-F-F
Group  19, HL_07480.2  has acceptance rules  -7.2433 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.2433 - AlignmentScore) +   3.0000 * CoreEdit <=  18.7897, method  6,TP   100.00%, TN    96.02%, min    96.02%,   3 3D sequences,     0 alignment sequences,   930 random sequences,   37 random matches,  7 NTs, cWW-tSH-F-F-F
Group  20, HL_07583.1  has acceptance rules -13.2273 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-13.2273 - AlignmentScore) +   3.0000 * CoreEdit <=  14.9784, method  6,TP   100.00%, TN    96.02%, min    96.02%,   2 3D sequences,     0 alignment sequences,   805 random sequences,   32 random matches, 12 NTs, cWW-cWW-F-F-F-F-F-F-F-F
Group  21, HL_07886.3  has acceptance rules  -5.4345 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.4345 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    87.83%, min    87.83%,   6 3D sequences,     0 alignment sequences,  7264 random sequences,  884 random matches,  5 NTs, cWW-F-F-F
Group  22, HL_07903.1  has acceptance rules  -9.1715 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.1715 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.06%, min    97.06%,   1 3D sequences,     0 alignment sequences,    68 random sequences,    2 random matches, 13 NTs, cWW-cWW-F-F-F-F-F-F-F-F-F
Group  23, HL_07951.3  has acceptance rules  -9.7335 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.7335 - AlignmentScore) +   3.0000 * CoreEdit <=  12.2759, method  6,TP   100.00%, TN    96.01%, min    96.01%,   4 3D sequences,     0 alignment sequences,  4058 random sequences,  162 random matches,  4 NTs, cWW-F-F
Group  24, HL_08100.1  has acceptance rules  -5.0957 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.0957 - AlignmentScore) +   3.0000 * CoreEdit <=  10.0841, method  6,TP   100.00%, TN    96.00%, min    96.00%,   4 3D sequences,     0 alignment sequences,  6329 random sequences,  253 random matches,  5 NTs, cWW-F-F-F
Group  25, HL_08510.1  has acceptance rules  -5.3349 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.3349 - AlignmentScore) +   3.0000 * CoreEdit <=  17.1518, method  6,TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences,  2325 random sequences,   93 random matches,  8 NTs, cWW-F-F-cSH-F-F
Group  26, HL_08602.1  has acceptance rules  -9.3260 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.3260 - AlignmentScore) +   3.0000 * CoreEdit <=  19.0768, method  6,TP   100.00%, TN    96.02%, min    96.02%,   1 3D sequences,     0 alignment sequences,   352 random sequences,   14 random matches, 11 NTs, cWW-cSS-F-cSS-F-F-F-F-F
Group  27, HL_09260.2  has acceptance rules -10.2392 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-10.2392 - AlignmentScore) +   3.0000 * CoreEdit <=  16.6902, method  6,TP   100.00%, TN    95.98%, min    95.98%,   3 3D sequences,     0 alignment sequences,  1170 random sequences,   47 random matches,  6 NTs, cWW-F-F-F-F
Group  28, HL_09452.1  has acceptance rules  -8.7143 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.7143 - AlignmentScore) +   3.0000 * CoreEdit <=  11.6062, method  6,TP   100.00%, TN    96.01%, min    96.01%,   3 3D sequences,     0 alignment sequences,  4185 random sequences,  167 random matches,  5 NTs, cWW-F-F-F
Group  29, HL_10453.3  has acceptance rules  -5.5959 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.5959 - AlignmentScore) +   3.0000 * CoreEdit <=  11.0611, method  6,TP   100.00%, TN    96.00%, min    96.00%,   9 3D sequences,     0 alignment sequences,  6725 random sequences,  269 random matches,  7 NTs, cWW-F-F-F-F-F
Group  30, HL_10456.1  has acceptance rules  -7.6384 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.6384 - 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, 17 NTs, cWW-F-cWW-tWW-F-tHW-F-F-F-F-F-F-F
Group  31, HL_10540.1  has acceptance rules  -7.2067 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.2067 - AlignmentScore) +   3.0000 * CoreEdit <=  10.3952, method  6,TP   100.00%, TN    95.83%, min    95.83%,   2 3D sequences,     0 alignment sequences,  6645 random sequences,  277 random matches,  7 NTs, cWW-F-F-F-F-F
Group  32, HL_11542.1  has acceptance rules  -9.5311 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.5311 - AlignmentScore) +   3.0000 * CoreEdit <=  17.9595, method  6,TP   100.00%, TN    95.98%, min    95.98%,   1 3D sequences,     0 alignment sequences,   498 random sequences,   20 random matches, 10 NTs, cWW-tSH-F-F-F-F-F-F
Group  33, HL_12758.3  has acceptance rules -10.6766 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-10.6766 - 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, 19 NTs, cWW-tSH-F-cHW-F-F-cWH-cHW-cWH-cHW-cWH-cWH-F-tSH-F-cHW-F-cWH-cWH
Group  34, HL_12870.1  has acceptance rules  -7.4651 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.4651 - AlignmentScore) +   3.0000 * CoreEdit <=  18.1504, method  6,TP   100.00%, TN    96.17%, min    96.17%,   1 3D sequences,     0 alignment sequences,   235 random sequences,    9 random matches, 12 NTs, cWW-tHW-F-F-F-F-F-F-F-F-F
Group  35, HL_13189.1  has acceptance rules  -5.8431 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.8431 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    68.64%, min    68.64%,   2 3D sequences,     0 alignment sequences,  6332 random sequences, 1986 random matches,  4 NTs, cWW-F-F
Group  36, HL_13529.1  has acceptance rules  -6.4438 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.4438 - AlignmentScore) +   3.0000 * CoreEdit <=  11.4732, method  6,TP   100.00%, TN    95.97%, min    95.97%,   2 3D sequences,     0 alignment sequences,  7441 random sequences,  300 random matches,  7 NTs, cWW-F-F-F-F
Group  37, HL_13963.3  has acceptance rules  -6.3650 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.3650 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    92.41%, min    92.41%,   4 3D sequences,     0 alignment sequences,  7534 random sequences,  572 random matches,  4 NTs, cWW-F-F
Group  38, HL_13971.1  has acceptance rules  -6.3144 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.3144 - AlignmentScore) +   3.0000 * CoreEdit <=  25.0000, method  1,TP   100.00%, TN   100.00%, min   100.00%,   2 3D sequences,     0 alignment sequences,    17 random sequences,    0 random matches, 14 NTs, cWW-cWS-F-tSW-F-tSH-tSH-cWW-F-F
Group  39, HL_14757.1  has acceptance rules  -8.5917 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.5917 - 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-cWW-F-F-tSW-tWW-cWW-tHW-tSW-F-cWH-F
Group  40, HL_15118.1  has acceptance rules  -8.5594 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.5594 - AlignmentScore) +   3.0000 * CoreEdit <=  19.7603, method  6,TP   100.00%, TN    96.07%, min    96.07%,   1 3D sequences,     0 alignment sequences,   636 random sequences,   25 random matches, 11 NTs, cWW-F-F-F-F-F-F-F-F-F
Group  41, HL_15574.1  has acceptance rules  -5.1260 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.1260 - AlignmentScore) +   3.0000 * CoreEdit <=   9.6176, method  6,TP   100.00%, TN    95.55%, min    95.55%,   2 3D sequences,     0 alignment sequences,  5936 random sequences,  264 random matches,  7 NTs, cWW-F-F-F-F-F
Group  42, HL_15802.1  has acceptance rules  -6.2013 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.2013 - AlignmentScore) +   3.0000 * CoreEdit <=  15.9950, method  6,TP   100.00%, TN    96.01%, min    96.01%,   1 3D sequences,     0 alignment sequences,  4737 random sequences,  189 random matches,  7 NTs, cWW-cWW-F-F-F
Group  43, HL_16398.2  has acceptance rules -12.1502 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-12.1502 - AlignmentScore) +   3.0000 * CoreEdit <=  17.0678, method  6,TP   100.00%, TN    96.04%, min    96.04%,   3 3D sequences,     0 alignment sequences,   984 random sequences,   39 random matches,  8 NTs, cWW-F-F-F-F-F-F
Group  44, HL_16991.1  has acceptance rules  -6.4750 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.4750 - AlignmentScore) +   3.0000 * CoreEdit <=  19.5119, method  6,TP   100.00%, TN    95.97%, min    95.97%,   1 3D sequences,     0 alignment sequences,  1165 random sequences,   47 random matches,  8 NTs, cWW-cWH-cWH-F-cWH-F
Group  45, HL_18423.1  has acceptance rules  -9.2929 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.2929 - AlignmentScore) +   3.0000 * CoreEdit <=  16.5357, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences,  3651 random sequences,  146 random matches,  7 NTs, cWW-tSH-tHS-F
Group  46, HL_18565.1  has acceptance rules  -5.1692 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.1692 - AlignmentScore) +   3.0000 * CoreEdit <=  16.5350, method  6,TP   100.00%, TN    95.96%, min    95.96%,   2 3D sequences,     0 alignment sequences,  5246 random sequences,  212 random matches,  8 NTs, cWW-cWW-F-F-F-F
Group  47, HL_18978.1  has acceptance rules  -6.1826 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.1826 - AlignmentScore) +   3.0000 * CoreEdit <=  18.7709, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences,  2798 random sequences,  112 random matches,  9 NTs, cWW-F-F-tHW-F-F-F
Group  48, HL_19210.3  has acceptance rules  -4.8159 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.8159 - AlignmentScore) +   3.0000 * CoreEdit <=  18.0846, method  6,TP   100.00%, TN    96.00%, min    96.00%,   7 3D sequences,     0 alignment sequences,  1798 random sequences,   72 random matches, 10 NTs, cWW-F-F-F-F-F-F-F-F
Group  49, HL_20167.2  has acceptance rules  -5.5702 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.5702 - AlignmentScore) +   3.0000 * CoreEdit <=  13.4378, method  6,TP   100.00%, TN    96.00%, min    96.00%,  10 3D sequences,     0 alignment sequences,  7224 random sequences,  289 random matches,  8 NTs, cWW-F-F-F-F-F-F
Group  50, HL_20535.2  has acceptance rules -10.4018 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-10.4018 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    94.69%, min    94.69%,   3 3D sequences,     0 alignment sequences,  8455 random sequences,  449 random matches,  6 NTs, cWW-F-F-F-F
Group  51, HL_20743.5  has acceptance rules  -5.3669 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.3669 - AlignmentScore) +   3.0000 * CoreEdit <=  14.9945, method  6,TP   100.00%, TN    96.00%, min    96.00%,   7 3D sequences,     0 alignment sequences,  5297 random sequences,  212 random matches,  8 NTs, cWW-cWW-F-F-F-F
Group  52, HL_20751.2  has acceptance rules  -8.6242 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.6242 - AlignmentScore) +   3.0000 * CoreEdit <=  19.2844, method  6,TP   100.00%, TN    95.99%, min    95.99%,   3 3D sequences,     0 alignment sequences,   324 random sequences,   13 random matches, 13 NTs, cWW-tHW-F-F-F-F-F-F-F-F-F
Group  53, HL_20781.1  has acceptance rules  -7.8663 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.8663 - AlignmentScore) +   3.0000 * CoreEdit <=  13.5768, method  6,TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences,  2420 random sequences,   97 random matches, 10 NTs, cWW-F-F-F-F-F-F-F-F
Group  54, HL_20811.4  has acceptance rules  -7.5199 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.5199 - AlignmentScore) +   3.0000 * CoreEdit <=  10.4270, method  6,TP   100.00%, TN    96.00%, min    96.00%,  14 3D sequences,     0 alignment sequences,  8130 random sequences,  325 random matches,  5 NTs, cWW-cWS-F
Group  55, HL_21372.1  has acceptance rules  -8.2538 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.2538 - AlignmentScore) +   3.0000 * CoreEdit <=  12.1187, method  6,TP   100.00%, TN    95.98%, min    95.98%,   2 3D sequences,     0 alignment sequences,  4607 random sequences,  185 random matches,  5 NTs, cWW-F-cSH-F-F
Group  56, HL_21400.1  has acceptance rules  -7.0896 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.0896 - 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-tWH-tSW-cWW-cWH-cHW-cWH-cWH-cHW-cWH-cHW-cWH-cWH-cWH-cWH-cWH
Group  57, HL_22135.1  has acceptance rules  -3.2074 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.2074 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    85.44%, min    85.44%,   1 3D sequences,     0 alignment sequences,  4801 random sequences,  699 random matches,  4 NTs, cWW-F-F
Group  58, HL_22584.6  has acceptance rules  -2.3968 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -2.3968 - AlignmentScore) +   3.0000 * CoreEdit <=  11.2864, method  6,TP   100.00%, TN    96.01%, min    96.01%,  26 3D sequences,     0 alignment sequences,  4286 random sequences,  171 random matches,  5 NTs, cWW-tSW-F
Group  59, HL_22622.1  has acceptance rules  -7.4736 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.4736 - AlignmentScore) +   3.0000 * CoreEdit <=  11.5105, method  6,TP   100.00%, TN    95.99%, min    95.99%,   2 3D sequences,     0 alignment sequences,  4588 random sequences,  184 random matches,  6 NTs, cWW-F-F-F-F-F
Group  60, HL_23010.1  has acceptance rules  -7.8097 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.8097 - AlignmentScore) +   3.0000 * CoreEdit <=  16.9613, method  6,TP   100.00%, TN    95.98%, min    95.98%,   1 3D sequences,     0 alignment sequences,  1814 random sequences,   73 random matches,  8 NTs, cWW-F-F-F-F-F-F
Group  61, HL_23115.1  has acceptance rules  -6.7180 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.7180 - AlignmentScore) +   3.0000 * CoreEdit <=  19.0255, method  6,TP   100.00%, TN    95.96%, min    95.96%,   2 3D sequences,     0 alignment sequences,  1040 random sequences,   42 random matches,  7 NTs, cWW-F-F-F-F-F
Group  62, HL_23509.1  has acceptance rules  -5.4579 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.4579 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    96.35%, min    96.35%,   1 3D sequences,     0 alignment sequences,   630 random sequences,   23 random matches, 11 NTs, cSH-F-F-F-F-F-F-F-F-F
Group  63, HL_24792.1  has acceptance rules  -6.4227 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.4227 - AlignmentScore) +   3.0000 * CoreEdit <=  17.7526, method  6,TP   100.00%, TN    95.87%, min    95.87%,   1 3D sequences,     0 alignment sequences,  1042 random sequences,   43 random matches,  6 NTs, cWW-cWS-F-F-F
Group  64, HL_25061.1  has acceptance rules  -8.7371 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.7371 - AlignmentScore) +   3.0000 * CoreEdit <=  13.0763, method  6,TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences,  6150 random sequences,  246 random matches,  5 NTs, cWW-F-F-F-F
Group  65, HL_25847.2  has acceptance rules  -4.3430 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.3430 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.06%, min    97.06%,   3 3D sequences,     0 alignment sequences,  2143 random sequences,   63 random matches, 10 NTs, cWW-F-cSH-tHW-F-F-F
Group  66, HL_25967.2  has acceptance rules  -4.4355 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.4355 - AlignmentScore) +   3.0000 * CoreEdit <=  12.3584, method  6,TP   100.00%, TN    96.00%, min    96.00%,   3 3D sequences,     0 alignment sequences,  5226 random sequences,  209 random matches,  7 NTs, cWW-cWW-F-F-F
Group  67, HL_26631.1  has acceptance rules  -2.5658 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -2.5658 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    90.40%, min    90.40%,   2 3D sequences,     0 alignment sequences,  3011 random sequences,  289 random matches,  5 NTs, cWW-F-F-F
Group  68, HL_26934.1  has acceptance rules  -3.7607 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.7607 - AlignmentScore) +   3.0000 * CoreEdit <=  16.0515, method  6,TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences,  5181 random sequences,  208 random matches,  8 NTs, cWW-F-F-F-F-F-F
Group  69, HL_27483.1  has acceptance rules  -4.1923 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.1923 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    80.97%, min    80.97%,   2 3D sequences,     0 alignment sequences,  6159 random sequences, 1172 random matches,  4 NTs, cWW-F
Group  70, HL_27670.2  has acceptance rules  -5.4314 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.4314 - AlignmentScore) +   3.0000 * CoreEdit <=  13.0534, method  6,TP   100.00%, TN    95.99%, min    95.99%,  13 3D sequences,     0 alignment sequences,  5540 random sequences,  222 random matches,  6 NTs, cWW-tWH-F-F
Group  71, HL_28075.1  has acceptance rules  -7.8217 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.8217 - AlignmentScore) +   3.0000 * CoreEdit <=   9.8888, method  6,TP   100.00%, TN    96.00%, min    96.00%,   4 3D sequences,     0 alignment sequences,  7176 random sequences,  287 random matches,  7 NTs, cWW-F-F-F-F-F
Group  72, HL_28252.8  has acceptance rules  -2.3605 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -2.3605 - AlignmentScore) +   3.0000 * CoreEdit <=  15.3636, method  6,TP    97.86%, TN    96.02%, min    96.02%, 140 3D sequences,     0 alignment sequences,  1984 random sequences,   79 random matches,  9 NTs, cWW-tWH-F-F-F-F-F
Group  73, HL_28791.1  has acceptance rules  -3.7921 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.7921 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    95.03%, min    95.03%,   1 3D sequences,     0 alignment sequences,  3982 random sequences,  198 random matches,  6 NTs, cWW-F-F-F-F
Group  74, HL_29129.3  has acceptance rules  -6.8801 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.8801 - AlignmentScore) +   3.0000 * CoreEdit <=  17.0057, method  6,TP   100.00%, TN    95.96%, min    95.96%,   3 3D sequences,     0 alignment sequences,  2549 random sequences,  103 random matches,  8 NTs, cWW-tWH-F-F-F-F
Group  75, HL_29762.1  has acceptance rules  -9.0440 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.0440 - AlignmentScore) +   3.0000 * CoreEdit <=  17.3626, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences,  3401 random sequences,  136 random matches,  7 NTs, cWW-F-F-F-F-F
Group  76, HL_29958.1  has acceptance rules  -9.9378 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.9378 - AlignmentScore) +   3.0000 * CoreEdit <=  16.8165, method  6,TP   100.00%, TN    95.89%, min    95.89%,   1 3D sequences,     0 alignment sequences,   219 random sequences,    9 random matches, 10 NTs, cWW-F-F-F-F-F-F-F-F
Group  77, HL_29966.1  has acceptance rules  -4.4128 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.4128 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    89.96%, min    89.96%,   1 3D sequences,     0 alignment sequences,  4700 random sequences,  472 random matches,  5 NTs, cWW-F-F-F
Group  78, HL_30068.2  has acceptance rules  -6.0518 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.0518 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    95.53%, min    95.53%,  15 3D sequences,     0 alignment sequences,  6686 random sequences,  299 random matches,  6 NTs, cWW-F-F-F-F
Group  79, HL_30680.3  has acceptance rules  -6.4673 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.4673 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    95.43%, min    95.43%,  15 3D sequences,     0 alignment sequences,  5815 random sequences,  266 random matches,  7 NTs, cWW-F-F-F-F-F
Group  80, HL_31581.6  has acceptance rules  -7.1505 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.1505 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.55%, min    97.55%,   3 3D sequences,     0 alignment sequences,   611 random sequences,   15 random matches, 11 NTs, cWW-cHS-F-F-F-cWW-F-F-F
Group  81, HL_31585.4  has acceptance rules  -6.4455 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.4455 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    93.04%, min    93.04%,  20 3D sequences,     0 alignment sequences,  6175 random sequences,  430 random matches,  7 NTs, cWW-F-F-F-F-F
Group  82, HL_32346.4  has acceptance rules  -4.0119 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.0119 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    62.41%, min    62.41%,   9 3D sequences,     0 alignment sequences,  4634 random sequences, 1742 random matches,  3 NTs, cWW-F
Group  83, HL_32392.1  has acceptance rules  -3.6707 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.6707 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    84.55%, min    84.55%,   2 3D sequences,     0 alignment sequences,  5352 random sequences,  827 random matches,  4 NTs, cWW-F-F
Group  84, HL_32735.2  has acceptance rules  -3.6330 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.6330 - AlignmentScore) +   3.0000 * CoreEdit <=  16.8871, method  6,TP   100.00%, TN    95.98%, min    95.98%,   7 3D sequences,     0 alignment sequences,  1569 random sequences,   63 random matches,  9 NTs, cWW-tSH-F-F-F-F-F
Group  85, HL_33074.4  has acceptance rules  -1.8806 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -1.8806 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    98.31%, min    98.31%,  22 3D sequences,     0 alignment sequences,    59 random sequences,    1 random matches, 10 NTs, cWW-F-F-F-F-F-F-F-F
Group  86, HL_33983.1  has acceptance rules  -6.5674 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.5674 - AlignmentScore) +   3.0000 * CoreEdit <=  13.9010, method  6,TP   100.00%, TN    95.97%, min    95.97%,   1 3D sequences,     0 alignment sequences,  5528 random sequences,  223 random matches,  7 NTs, cWW-F-F-F-F-F
Group  87, HL_34617.5  has acceptance rules  -1.9414 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -1.9414 - AlignmentScore) +   3.0000 * CoreEdit <=   9.9780, method  6,TP    98.25%, TN    96.01%, min    96.01%,  57 3D sequences,     0 alignment sequences,  4484 random sequences,  179 random matches,  5 NTs, cWW-tSW-F
Group  88, HL_34964.1  has acceptance rules  -9.5519 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.5519 - AlignmentScore) +   3.0000 * CoreEdit <=  15.9197, method  6,TP   100.00%, TN    96.01%, min    96.01%,   2 3D sequences,     0 alignment sequences,  2682 random sequences,  107 random matches,  9 NTs, cWW-F-F-F-F-F
Group  89, HL_35354.1  has acceptance rules -10.3000 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-10.3000 - 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-cWH-cHW-F-cWH-cHW-F-F-tHH-cWH-tWW-cWH-F-tWW-cWH-F-cWH
Group  90, HL_35677.3  has acceptance rules  -7.3767 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.3767 - AlignmentScore) +   3.0000 * CoreEdit <=  15.3959, method  6,TP   100.00%, TN    95.99%, min    95.99%,   7 3D sequences,     0 alignment sequences,  4669 random sequences,  187 random matches,  9 NTs, cWW-F-F-F-F-F-F-F
Group  91, HL_35941.1  has acceptance rules  -3.7846 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.7846 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    76.86%, min    76.86%,   1 3D sequences,     0 alignment sequences,  5112 random sequences, 1183 random matches,  3 NTs, cWW-F
Group  92, HL_36335.1  has acceptance rules  -7.9142 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.9142 - AlignmentScore) +   3.0000 * CoreEdit <=  14.1322, method  6,TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences,  3997 random sequences,  160 random matches,  9 NTs, cWW-F-F-cSS-cSS-F
Group  93, HL_36684.4  has acceptance rules  -7.8135 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.8135 - AlignmentScore) +   3.0000 * CoreEdit <=  17.1174, method  6,TP   100.00%, TN    96.02%, min    96.02%,   7 3D sequences,     0 alignment sequences,  2187 random sequences,   87 random matches, 11 NTs, cWW-F-F-F-F-F-F-F-F-F
Group  94, HL_37344.1  has acceptance rules  -6.4857 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.4857 - AlignmentScore) +   3.0000 * CoreEdit <=  10.6064, method  6,TP   100.00%, TN    95.99%, min    95.99%,   2 3D sequences,     0 alignment sequences,  6952 random sequences,  279 random matches,  6 NTs, cWW-F-F
Group  95, HL_37369.2  has acceptance rules  -3.3463 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.3463 - AlignmentScore) +   3.0000 * CoreEdit <=  13.2390, method  6,TP   100.00%, TN    95.98%, min    95.98%,   9 3D sequences,     0 alignment sequences,  2883 random sequences,  116 random matches,  7 NTs, cWW-tSH-F-F-F
Group  96, HL_37824.7  has acceptance rules  -1.7593 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -1.7593 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5935, method  6,TP    97.42%, TN    95.93%, min    95.93%, 349 3D sequences,     0 alignment sequences,  4674 random sequences,  190 random matches,  6 NTs, cWW-F-F-F-F
Group  97, HL_38046.1  has acceptance rules  -6.5024 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.5024 - AlignmentScore) +   3.0000 * CoreEdit <=  14.5984, method  6,TP   100.00%, TN    95.98%, min    95.98%,   1 3D sequences,     0 alignment sequences,  4599 random sequences,  185 random matches,  8 NTs, cWW-F-F-F-F-F-F
Group  98, HL_38168.1  has acceptance rules  -4.9890 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.9890 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    81.17%, min    81.17%,   2 3D sequences,     0 alignment sequences,  6528 random sequences, 1229 random matches,  3 NTs, cWW-F
Group  99, HL_38649.1  has acceptance rules -10.1131 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-10.1131 - AlignmentScore) +   3.0000 * CoreEdit <=  16.7080, method  6,TP   100.00%, TN    96.00%, min    96.00%,   5 3D sequences,     0 alignment sequences,  2399 random sequences,   96 random matches, 10 NTs, cWW-tSH-F-F-F-F-F-F
Group 100, HL_38808.1  has acceptance rules  -8.9167 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.9167 - AlignmentScore) +   3.0000 * CoreEdit <=  12.9067, method  6,TP   100.00%, TN    95.97%, min    95.97%,   4 3D sequences,     0 alignment sequences,  6280 random sequences,  253 random matches,  4 NTs, cWW-cWW
Group 101, HL_38901.2  has acceptance rules  -4.8846 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.8846 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    76.36%, min    76.36%,   7 3D sequences,     0 alignment sequences,  5160 random sequences, 1220 random matches,  5 NTs, cWW-F-cSH
Group 102, HL_39243.1  has acceptance rules  -7.0068 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.0068 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    94.02%, min    94.02%,   2 3D sequences,     0 alignment sequences,  5919 random sequences,  354 random matches,  6 NTs, cWW-F-F-F-F
Group 103, HL_40252.4  has acceptance rules -10.2529 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-10.2529 - AlignmentScore) +   3.0000 * CoreEdit <=  16.3656, method  6,TP   100.00%, TN    95.99%, min    95.99%,   5 3D sequences,     0 alignment sequences,  2568 random sequences,  103 random matches,  7 NTs, cWW-tSH-cWS-F
Group 104, HL_41464.2  has acceptance rules  -8.0258 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.0258 - AlignmentScore) +   3.0000 * CoreEdit <=  10.8878, method  6,TP   100.00%, TN    95.99%, min    95.99%,   4 3D sequences,     0 alignment sequences,  7926 random sequences,  318 random matches,  7 NTs, cWW-F-F-F-F-F
Group 105, HL_41543.1  has acceptance rules  -8.8746 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.8746 - AlignmentScore) +   3.0000 * CoreEdit <=  18.0029, method  6,TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences,  2002 random sequences,   80 random matches, 10 NTs, cWW-F-F-F-F-F-F-F-F
Group 106, HL_41902.1  has acceptance rules  -6.6206 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.6206 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.36%, min    97.36%,   2 3D sequences,     0 alignment sequences,   606 random sequences,   16 random matches, 11 NTs, cWW-cWW-cWH-F-F-F-F-F
Group 107, HL_42046.2  has acceptance rules  -4.6378 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.6378 - AlignmentScore) +   3.0000 * CoreEdit <=  12.1166, method  6,TP   100.00%, TN    95.96%, min    95.96%,   5 3D sequences,     0 alignment sequences,  5398 random sequences,  218 random matches,  7 NTs, cWW-tSS-F-F-F
Group 108, HL_42998.2  has acceptance rules  -2.7314 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -2.7314 - AlignmentScore) +   3.0000 * CoreEdit <=  12.4599, method  6,TP   100.00%, TN    95.95%, min    95.95%,   7 3D sequences,     0 alignment sequences,  2321 random sequences,   94 random matches,  8 NTs, cWW-F-F-F-F-F-F
Group 109, HL_43517.1  has acceptance rules  -4.6523 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.6523 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    89.99%, min    89.99%,   2 3D sequences,     0 alignment sequences,  6135 random sequences,  614 random matches,  5 NTs, cWW-F-F-F
Group 110, HL_45175.1  has acceptance rules  -7.1333 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.1333 - AlignmentScore) +   3.0000 * CoreEdit <=  15.6574, method  6,TP   100.00%, TN    96.01%, min    96.01%,   5 3D sequences,     0 alignment sequences,  4111 random sequences,  164 random matches,  6 NTs, cWW-cWS-F-F
Group 111, HL_45785.1  has acceptance rules  -6.5157 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.5157 - AlignmentScore) +   3.0000 * CoreEdit <=  19.5425, method  6,TP   100.00%, TN    96.04%, min    96.04%,   2 3D sequences,     0 alignment sequences,   984 random sequences,   39 random matches, 10 NTs, cWW-F-F-F-F-cSH-F-F
Group 112, HL_46501.1  has acceptance rules  -4.3240 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.3240 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    87.12%, min    87.12%,   2 3D sequences,     0 alignment sequences,  5558 random sequences,  716 random matches,  5 NTs, cWW-cWS
Group 113, HL_47732.1  has acceptance rules  -6.8596 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.8596 - AlignmentScore) +   3.0000 * CoreEdit <=  16.3545, method  6,TP   100.00%, TN    95.97%, min    95.97%,   2 3D sequences,     0 alignment sequences,  1415 random sequences,   57 random matches,  8 NTs, cWW-F-F-F-F-F-F
Group 114, HL_47787.2  has acceptance rules  -3.7245 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.7245 - AlignmentScore) +   3.0000 * CoreEdit <=   9.9457, method  6,TP   100.00%, TN    96.01%, min    96.01%,  10 3D sequences,     0 alignment sequences,  5382 random sequences,  215 random matches,  6 NTs, cWW-F-F-F-F
Group 115, HL_47854.1  has acceptance rules  -4.9116 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.9116 - AlignmentScore) +   3.0000 * CoreEdit <=  12.3703, method  6,TP   100.00%, TN    95.81%, min    95.81%,   1 3D sequences,     0 alignment sequences,  5134 random sequences,  215 random matches,  6 NTs, cWW-F-F-F-F
Group 116, HL_48417.5  has acceptance rules  -5.9356 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.9356 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    79.33%, min    79.33%,  26 3D sequences,     0 alignment sequences,  8458 random sequences, 1748 random matches,  4 NTs, cWW-F-F
Group 117, HL_48778.2  has acceptance rules  -3.2002 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.2002 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    67.10%, min    67.10%,  46 3D sequences,     0 alignment sequences,  3881 random sequences, 1277 random matches,  3 NTs, cWW-F
Group 118, HL_49922.4  has acceptance rules  -4.0597 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.0597 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    95.09%, min    95.09%,  10 3D sequences,     0 alignment sequences,  6113 random sequences,  300 random matches,  5 NTs, cWW-F-F-F
Group 119, HL_49941.1  has acceptance rules  -8.0731 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.0731 - AlignmentScore) +   3.0000 * CoreEdit <=  18.0983, method  6,TP   100.00%, TN    95.98%, min    95.98%,   4 3D sequences,     0 alignment sequences,  2266 random sequences,   91 random matches,  7 NTs, cWW-F-F-F-F-F
Group 120, HL_50006.2  has acceptance rules  -8.2327 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.2327 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    81.03%, min    81.03%,   5 3D sequences,     0 alignment sequences,  7859 random sequences, 1491 random matches,  4 NTs, cWW-F-F
Group 121, HL_50318.1  has acceptance rules  -6.0162 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.0162 - AlignmentScore) +   3.0000 * CoreEdit <=  12.4472, method  6,TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences,  6916 random sequences,  277 random matches,  6 NTs, cWW-cSH-F-F
Group 122, HL_50418.1  has acceptance rules  -8.9410 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.9410 - AlignmentScore) +   3.0000 * CoreEdit <=  16.0662, method  6,TP   100.00%, TN    95.95%, min    95.95%,   3 3D sequences,     0 alignment sequences,  2195 random sequences,   89 random matches, 11 NTs, cWW-F-F-F-F-F-F-F-F-F
Group 123, HL_50537.6  has acceptance rules  -8.0828 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.0828 - AlignmentScore) +   3.0000 * CoreEdit <=  11.2790, method  6,TP   100.00%, TN    96.00%, min    96.00%,   4 3D sequences,     0 alignment sequences,  7957 random sequences,  318 random matches,  5 NTs, cWW-F-F-F
Group 124, HL_50779.4  has acceptance rules  -5.0734 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.0734 - AlignmentScore) +   3.0000 * CoreEdit <=  17.6188, method  6,TP   100.00%, TN    95.97%, min    95.97%,   4 3D sequences,     0 alignment sequences,  2505 random sequences,  101 random matches,  9 NTs, cWW-F-F-F-F-F-F-F
Group 125, HL_50851.1  has acceptance rules  -4.5507 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.5507 - AlignmentScore) +   3.0000 * CoreEdit <=  22.2069, method  8,TP   100.00%, TN    98.01%, min    98.01%,   1 3D sequences,     0 alignment sequences,   251 random sequences,    5 random matches,  9 NTs, cWW-cWH-cWH-cWH-cWH-F
Group 126, HL_50860.2  has acceptance rules  -4.6324 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.6324 - AlignmentScore) +   3.0000 * CoreEdit <=  16.0618, method  6,TP   100.00%, TN    96.00%, min    96.00%,   6 3D sequences,     0 alignment sequences,  4696 random sequences,  188 random matches,  9 NTs, cWW-F-cWH-F-F-F-F
Group 127, HL_51447.1  has acceptance rules  -4.9961 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.9961 - AlignmentScore) +   3.0000 * CoreEdit <=  11.5889, method  6,TP   100.00%, TN    95.98%, min    95.98%,   1 3D sequences,     0 alignment sequences,  3901 random sequences,  157 random matches,  7 NTs, cWW-F-F-F-F-F
Group 128, HL_51921.1  has acceptance rules -12.2799 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-12.2799 - AlignmentScore) +   3.0000 * CoreEdit <=  25.0000, method  1,TP   100.00%, TN   100.00%, min   100.00%,   2 3D sequences,     0 alignment sequences,     3 random sequences,    0 random matches, 18 NTs, cWW-tSH-tSS-tHS-F-F-F-F-F-F-F-F-F-F-F
Group 129, HL_52953.3  has acceptance rules  -4.2010 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.2010 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    87.85%, min    87.85%,   9 3D sequences,     0 alignment sequences,  3894 random sequences,  473 random matches,  6 NTs, cWW-F-F-F-F
Group 130, HL_53454.2  has acceptance rules  -8.1449 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.1449 - AlignmentScore) +   3.0000 * CoreEdit <=  15.0523, method  6,TP   100.00%, TN    95.98%, min    95.98%,   6 3D sequences,     0 alignment sequences,  4453 random sequences,  179 random matches,  9 NTs, cWW-tSH-F-F-F-F-F
Group 131, HL_53504.3  has acceptance rules  -9.3433 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.3433 - AlignmentScore) +   3.0000 * CoreEdit <=  13.3570, method  6,TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences,  4604 random sequences,  184 random matches, 10 NTs, cWW-tSH-F-F-F-F-F-F
Group 132, HL_53890.2  has acceptance rules  -6.1324 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.1324 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    70.39%, min    70.39%,  15 3D sequences,     0 alignment sequences,  6626 random sequences, 1962 random matches,  5 NTs, cWW-F-F-F
Group 133, HL_55195.3  has acceptance rules  -3.0127 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.0127 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    89.67%, min    89.67%,   6 3D sequences,     0 alignment sequences,  4916 random sequences,  508 random matches,  3 NTs, cWW-F
Group 134, HL_55305.1  has acceptance rules  -9.4071 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.4071 - AlignmentScore) +   3.0000 * CoreEdit <=  17.7621, method  6,TP   100.00%, TN    95.96%, min    95.96%,   2 3D sequences,     0 alignment sequences,   867 random sequences,   35 random matches,  5 NTs, cWW-F-F-F-F-F
Group 135, HL_55436.1  has acceptance rules  -8.0736 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.0736 - AlignmentScore) +   3.0000 * CoreEdit <=  16.4830, method  6,TP   100.00%, TN    96.00%, min    96.00%,   4 3D sequences,     0 alignment sequences,  3497 random sequences,  140 random matches, 10 NTs, cWW-F-F-F-F-F-F-F-F
Group 136, HL_56131.2  has acceptance rules  -7.2099 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.2099 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    68.39%, min    68.39%,   6 3D sequences,     0 alignment sequences,  7614 random sequences, 2407 random matches,  4 NTs, cWW-F-F
Group 137, HL_56334.1  has acceptance rules  -5.1222 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.1222 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    57.50%, min    57.50%,  16 3D sequences,     0 alignment sequences,  5023 random sequences, 2135 random matches,  3 NTs, cWW-F
Group 138, HL_56676.1  has acceptance rules  -4.4762 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.4762 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    94.45%, min    94.45%,   2 3D sequences,     0 alignment sequences,  5266 random sequences,  292 random matches,  6 NTs, cWW-F-F
Group 139, HL_57176.2  has acceptance rules  -5.5987 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.5987 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    84.01%, min    84.01%,  14 3D sequences,     0 alignment sequences,  4983 random sequences,  797 random matches,  5 NTs, cWW-F-F-F
Group 140, HL_57863.1  has acceptance rules  -5.0183 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.0183 - AlignmentScore) +   3.0000 * CoreEdit <=  17.5413, method  6,TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences,  4047 random sequences,  162 random matches,  8 NTs, cWW-F-F-cWH-cWH-F
Group 141, HL_57875.1  has acceptance rules  -5.5231 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.5231 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    82.70%, min    82.70%,   5 3D sequences,     0 alignment sequences,  6024 random sequences, 1042 random matches,  4 NTs, cWW-F-F
Group 142, HL_58224.1  has acceptance rules  -6.6948 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.6948 - AlignmentScore) +   3.0000 * CoreEdit <=  17.4931, method  6,TP   100.00%, TN    95.93%, min    95.93%,   1 3D sequences,     0 alignment sequences,  3316 random sequences,  135 random matches,  7 NTs, cWW-F-F-F-F-F
Group 143, HL_58539.1  has acceptance rules -10.4256 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-10.4256 - AlignmentScore) +   3.0000 * CoreEdit <=  20.8947, method  8,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences,    25 random sequences,    1 random matches, 13 NTs, cWW-tWS-F-tHW-F-F-F-F-F-F-F-F
Group 144, HL_59330.1  has acceptance rules  -4.4306 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.4306 - AlignmentScore) +   3.0000 * CoreEdit <=  15.8070, method  6,TP   100.00%, TN    95.96%, min    95.96%,   1 3D sequences,     0 alignment sequences,  3636 random sequences,  147 random matches,  7 NTs, cWW-F-F-F-F-F
Group 145, HL_59564.1  has acceptance rules -15.5353 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-15.5353 - 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-F-cSS-F-cSS-F-F-F-F-F-F-F-F-F-F-F-F
Group 146, HL_59735.5  has acceptance rules  -5.3444 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.3444 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    93.84%, min    93.84%,   2 3D sequences,     0 alignment sequences,  4029 random sequences,  248 random matches,  7 NTs, cWW-F-F-F-F-F
Group 147, HL_59843.1  has acceptance rules  -5.7478 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.7478 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    91.05%, min    91.05%,   2 3D sequences,     0 alignment sequences,  6593 random sequences,  590 random matches,  6 NTs, cWW-F-F-F-F
Group 148, HL_60266.1  has acceptance rules  -8.2590 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.2590 - AlignmentScore) +   3.0000 * CoreEdit <=  15.9149, method  6,TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences,  3471 random sequences,  139 random matches,  9 NTs, cWW-cWW-tWH-F-F-F-F
Group 149, HL_60293.1  has acceptance rules  -8.3980 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.3980 - 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, 18 NTs, cWW-cWH-F-cWH-cHW-cHW-cWH-cHW-cWH-F-cWH-cWH-cWH-F
Group 150, HL_60914.1  has acceptance rules  -3.2509 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.2509 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    85.07%, min    85.07%,   1 3D sequences,     0 alignment sequences,  4670 random sequences,  697 random matches,  3 NTs, cWW-F
Group 151, HL_61996.2  has acceptance rules  -5.8170 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.8170 - AlignmentScore) +   3.0000 * CoreEdit <=  15.8167, method  6,TP   100.00%, TN    96.01%, min    96.01%,   8 3D sequences,     0 alignment sequences,  5482 random sequences,  219 random matches,  7 NTs, cWW-tWH-F-F-F
Group 152, HL_62934.1  has acceptance rules  -5.4339 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.4339 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    92.96%, min    92.96%,   2 3D sequences,     0 alignment sequences,  6510 random sequences,  458 random matches,  6 NTs, cWW-tSH-F
Group 153, HL_63355.1  has acceptance rules  -7.7878 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.7878 - AlignmentScore) +   3.0000 * CoreEdit <=  22.8245, method  8,TP   100.00%, TN    97.98%, min    97.98%,   1 3D sequences,     0 alignment sequences,   198 random sequences,    4 random matches, 13 NTs, cWW-F-F-F-F-F-F-F-F-F-F-F
Group 154, HL_64292.1  has acceptance rules -15.8767 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-15.8767 - AlignmentScore) +   3.0000 * CoreEdit <=  16.1819, method  6,TP   100.00%, TN    97.14%, min    97.14%,   2 3D sequences,     0 alignment sequences,    35 random sequences,    1 random matches, 10 NTs, cWW-F-F-F-F-F-F-F-F
Group 155, HL_64690.6  has acceptance rules  -6.4251 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.4251 - AlignmentScore) +   3.0000 * CoreEdit <=  12.8213, method  6,TP   100.00%, TN    95.99%, min    95.99%,   9 3D sequences,     0 alignment sequences,  6361 random sequences,  255 random matches,  8 NTs, cWW-cSW-F-F-F-F
Group 156, HL_65313.1  has acceptance rules  -4.3904 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.3904 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    92.02%, min    92.02%,   1 3D sequences,     0 alignment sequences,  4387 random sequences,  350 random matches,  5 NTs, cWW-F-F-F
Group 157, HL_65794.5  has acceptance rules  -4.4744 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.4744 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    88.49%, min    88.49%,  14 3D sequences,     0 alignment sequences,  5107 random sequences,  588 random matches,  6 NTs, cWW-F-F-F-F
Group 158, HL_66103.1  has acceptance rules  -6.7883 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.7883 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    92.50%, min    92.50%,   2 3D sequences,     0 alignment sequences,  7038 random sequences,  528 random matches,  4 NTs, cWW-F-F
Group 159, HL_66482.1  has acceptance rules -11.3758 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-11.3758 - 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-cWW-tWW-F-F-tWH-F-F-F-F-F-F-F-F
Group 160, HL_66853.7  has acceptance rules  -7.3434 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.3434 - AlignmentScore) +   3.0000 * CoreEdit <=  16.3733, method  6,TP   100.00%, TN    96.00%, min    96.00%,  11 3D sequences,     0 alignment sequences,  5319 random sequences,  213 random matches,  7 NTs, cWW-cWS-F-cSH
Group 161, HL_67079.1  has acceptance rules -10.6132 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-10.6132 - AlignmentScore) +   3.0000 * CoreEdit <=  15.9464, method  6,TP   100.00%, TN    96.01%, min    96.01%,   4 3D sequences,     0 alignment sequences,  4812 random sequences,  192 random matches,  9 NTs, cWW-F-F-F-F-F-F-F
Group 162, HL_67407.5  has acceptance rules  -7.1199 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.1199 - AlignmentScore) +   3.0000 * CoreEdit <=  19.5708, method  6,TP   100.00%, TN    95.97%, min    95.97%,  10 3D sequences,     0 alignment sequences,  2233 random sequences,   90 random matches, 10 NTs, cWW-F-F-F-F-F-F-F-F
Group 163, HL_67667.2  has acceptance rules  -4.3941 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.3941 - AlignmentScore) +   3.0000 * CoreEdit <=  10.6925, method  6,TP   100.00%, TN    95.98%, min    95.98%,   3 3D sequences,     0 alignment sequences,  3708 random sequences,  149 random matches,  4 NTs, cWW-F-F
Group 164, HL_68257.1  has acceptance rules  -9.0016 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.0016 - AlignmentScore) +   3.0000 * CoreEdit <=  18.1115, method  6,TP   100.00%, TN    96.01%, min    96.01%,   2 3D sequences,     0 alignment sequences,  2105 random sequences,   84 random matches, 11 NTs, cWW-F-F-F-F-F-F-F-F
Group 165, HL_68572.1  has acceptance rules -14.1290 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-14.1290 - AlignmentScore) +   3.0000 * CoreEdit <=  16.6867, method  6,TP   100.00%, TN    96.04%, min    96.04%,   3 3D sequences,     0 alignment sequences,   656 random sequences,   26 random matches,  9 NTs, cWW-F-F-F-F-F-F-F
Group 166, HL_68767.1  has acceptance rules  -8.2952 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.2952 - AlignmentScore) +   3.0000 * CoreEdit <=  18.8854, method  6,TP   100.00%, TN    96.03%, min    96.03%,   3 3D sequences,     0 alignment sequences,   756 random sequences,   30 random matches,  8 NTs, cWW-cWS-tSH-cWS-F
Group 167, HL_69139.1  has acceptance rules -10.0077 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-10.0077 - AlignmentScore) +   3.0000 * CoreEdit <=  15.1646, method  6,TP   100.00%, TN    95.98%, min    95.98%,   2 3D sequences,     0 alignment sequences,  2864 random sequences,  115 random matches,  9 NTs, cWW-F-F-F-F-F-F-F-F
Group 168, HL_69752.2  has acceptance rules  -5.4738 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.4738 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    76.63%, min    76.63%,   7 3D sequences,     0 alignment sequences,  5952 random sequences, 1391 random matches,  3 NTs, cWW-F
Group 169, HL_70658.1  has acceptance rules -10.7751 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-10.7751 - AlignmentScore) +   3.0000 * CoreEdit <=  19.1238, method  6,TP   100.00%, TN    95.98%, min    95.98%,   2 3D sequences,     0 alignment sequences,  1367 random sequences,   55 random matches, 12 NTs, cWW-F-F-F-F-F-F-F-F-F
Group 170, HL_70751.1  has acceptance rules  -6.7470 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.7470 - AlignmentScore) +   3.0000 * CoreEdit <=  18.0784, method  6,TP   100.00%, TN    95.87%, min    95.87%,   1 3D sequences,     0 alignment sequences,  1236 random sequences,   51 random matches, 11 NTs, cWW-F-F-F-F-F-F-F-F-F
Group 171, HL_70782.2  has acceptance rules  -6.6747 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.6747 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    62.65%, min    62.65%,   4 3D sequences,     0 alignment sequences,  6263 random sequences, 2339 random matches,  3 NTs, cWW-F
Group 172, HL_71391.1  has acceptance rules  -3.7990 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.7990 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    93.24%, min    93.24%,   2 3D sequences,     0 alignment sequences,  5414 random sequences,  366 random matches,  5 NTs, cWW-F-F-F-F
Group 173, HL_72628.1  has acceptance rules  -5.6175 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.6175 - AlignmentScore) +   3.0000 * CoreEdit <=  13.5743, method  6,TP   100.00%, TN    95.92%, min    95.92%,   1 3D sequences,     0 alignment sequences,  4825 random sequences,  197 random matches,  8 NTs, cWW-tSH-F-F-F-F
Group 174, HL_73183.1  has acceptance rules -10.2221 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-10.2221 - AlignmentScore) +   3.0000 * CoreEdit <=  19.4567, method  6,TP   100.00%, TN    96.10%, min    96.10%,   2 3D sequences,     0 alignment sequences,   282 random sequences,   11 random matches, 14 NTs, cWW-tSH-tHW-F-F-F-F-F-F-F-F-F
Group 175, HL_73247.1  has acceptance rules  -8.5392 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.5392 - AlignmentScore) +   3.0000 * CoreEdit <=  22.6436, method  8,TP   100.00%, TN    98.63%, min    98.63%,   3 3D sequences,     0 alignment sequences,    73 random sequences,    1 random matches, 15 NTs, cWW-F-tWH-F-F-F-F-F-F-F-F-F-F
Group 176, HL_73255.1  has acceptance rules  -7.7360 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.7360 - AlignmentScore) +   3.0000 * CoreEdit <=  15.2785, method  6,TP   100.00%, TN    95.99%, min    95.99%,   2 3D sequences,     0 alignment sequences,  2891 random sequences,  116 random matches,  6 NTs, cWW-F-F-F-F-F-F
Group 177, HL_73266.9  has acceptance rules  -4.7945 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.7945 - AlignmentScore) +   3.0000 * CoreEdit <=  14.4850, method  6,TP   100.00%, TN    96.00%, min    96.00%,  13 3D sequences,     0 alignment sequences,  3923 random sequences,  157 random matches,  9 NTs, cWW-F-F-cSW-cSH-F
Group 178, HL_73916.1  has acceptance rules -26.3197 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-26.3197 - 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, 37 NTs, cWW-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F
Group 179, HL_74055.2  has acceptance rules  -6.1388 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.1388 - AlignmentScore) +   3.0000 * CoreEdit <=  21.8795, method  8,TP   100.00%, TN    97.94%, min    97.94%,   7 3D sequences,     0 alignment sequences,    97 random sequences,    2 random matches, 13 NTs, cWW-tWH-cWH-tSH-tHW-tHW-tSW
Group 180, HL_74292.1  has acceptance rules  -7.0758 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.0758 - AlignmentScore) +   3.0000 * CoreEdit <=  16.3944, method  6,TP   100.00%, TN    95.13%, min    95.13%,   1 3D sequences,     0 alignment sequences,  1971 random sequences,   96 random matches, 10 NTs, cWW-F-F-F-F-F-F-F-F
Group 181, HL_74379.3  has acceptance rules  -9.4399 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.4399 - AlignmentScore) +   3.0000 * CoreEdit <=  19.9432, method  6,TP   100.00%, TN    95.96%, min    95.96%,   2 3D sequences,     0 alignment sequences,   991 random sequences,   40 random matches,  9 NTs, cWW-F-F-cSS-cSS-F-F-F
Group 182, HL_75293.5  has acceptance rules  -8.3134 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.3134 - AlignmentScore) +   3.0000 * CoreEdit <=  14.9588, method  6,TP   100.00%, TN    96.00%, min    96.00%,  11 3D sequences,     0 alignment sequences,  5526 random sequences,  221 random matches, 10 NTs, cWW-F-F-F-F-F-F-F-F
Group 183, HL_75660.5  has acceptance rules  -4.5368 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.5368 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    61.35%, min    61.35%,  19 3D sequences,     0 alignment sequences,  5586 random sequences, 2159 random matches,  3 NTs, cWW-F
Group 184, HL_76094.1  has acceptance rules  -2.8581 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -2.8581 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    87.81%, min    87.81%,   1 3D sequences,     0 alignment sequences,  3133 random sequences,  382 random matches,  5 NTs, cWW-cWS-F-F
Group 185, HL_77082.1  has acceptance rules  -7.5076 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.5076 - AlignmentScore) +   3.0000 * CoreEdit <=  11.1227, method  6,TP   100.00%, TN    96.00%, min    96.00%,   8 3D sequences,     0 alignment sequences,  6456 random sequences,  258 random matches,  8 NTs, cWW-F-F-F-F-F-F
Group 186, HL_77436.5  has acceptance rules  -6.2451 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.2451 - AlignmentScore) +   3.0000 * CoreEdit <=   9.7107, method  6,TP   100.00%, TN    95.98%, min    95.98%,  23 3D sequences,     0 alignment sequences,  7941 random sequences,  319 random matches,  7 NTs, cWW-F-F-F-F-F
Group 187, HL_77600.2  has acceptance rules  -9.7460 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.7460 - AlignmentScore) +   3.0000 * CoreEdit <=  10.2193, method  6,TP   100.00%, TN    96.00%, min    96.00%,  10 3D sequences,     0 alignment sequences,  4906 random sequences,  196 random matches,  7 NTs, cWW-F-F-F-F-F
Group 188, HL_78197.1  has acceptance rules  -7.7357 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.7357 - AlignmentScore) +   3.0000 * CoreEdit <=  10.3581, method  6,TP   100.00%, TN    95.84%, min    95.84%,   5 3D sequences,     0 alignment sequences,  6491 random sequences,  270 random matches,  8 NTs, cWW-F-F-F-F-F-F
Group 189, HL_78284.1  has acceptance rules -10.7410 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-10.7410 - AlignmentScore) +   3.0000 * CoreEdit <=  17.8367, method  6,TP   100.00%, TN    95.95%, min    95.95%,   2 3D sequences,     0 alignment sequences,  1851 random sequences,   75 random matches, 10 NTs, cWW-F-F-F-F-F-F-F-F-F-F
Group 190, HL_78347.4  has acceptance rules  -8.0569 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.0569 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    95.86%, min    95.86%,   9 3D sequences,     0 alignment sequences,  8485 random sequences,  351 random matches,  6 NTs, cWW-F-F-F-F
Group 191, HL_78677.1  has acceptance rules  -3.8850 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.8850 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    70.30%, min    70.30%,   2 3D sequences,     0 alignment sequences,  4892 random sequences, 1453 random matches,  3 NTs, cWW-F-F
Group 192, HL_80008.1  has acceptance rules  -6.4953 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.4953 - AlignmentScore) +   3.0000 * CoreEdit <=  13.4998, method  6,TP   100.00%, TN    95.94%, min    95.94%,   1 3D sequences,     0 alignment sequences,  4457 random sequences,  181 random matches,  8 NTs, cWW-F-F-F-cSH-F
Group 193, HL_80241.1  has acceptance rules  -6.8457 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.8457 - AlignmentScore) +   3.0000 * CoreEdit <=  12.9353, method  6,TP   100.00%, TN    95.95%, min    95.95%,   2 3D sequences,     0 alignment sequences,  3528 random sequences,  143 random matches,  9 NTs, cWW-F-F-F-F-F-F-F
Group 194, HL_80362.1  has acceptance rules  -7.0681 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.0681 - AlignmentScore) +   3.0000 * CoreEdit <=  14.1065, method  6,TP   100.00%, TN    95.97%, min    95.97%,   1 3D sequences,     0 alignment sequences,  3377 random sequences,  136 random matches,  5 NTs, cWW-F-F-F
Group 195, HL_80411.1  has acceptance rules  -8.2707 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.2707 - AlignmentScore) +   3.0000 * CoreEdit <=  17.9599, method  6,TP   100.00%, TN    96.03%, min    96.03%,   1 3D sequences,     0 alignment sequences,   931 random sequences,   37 random matches,  9 NTs, cWW-F-cSH-F-F-F-F
Group 196, HL_80599.2  has acceptance rules  -5.2987 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.2987 - AlignmentScore) +   3.0000 * CoreEdit <=  17.8620, method  6,TP   100.00%, TN    96.01%, min    96.01%,   3 3D sequences,     0 alignment sequences,  3262 random sequences,  130 random matches,  9 NTs, cWW-F-F-F-F-F-F-F
Group 197, HL_80709.3  has acceptance rules  -3.1784 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.1784 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    80.74%, min    80.74%,  11 3D sequences,     0 alignment sequences,  3723 random sequences,  717 random matches,  5 NTs, cWW-F-F-F
Group 198, HL_80922.2  has acceptance rules  -7.5586 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.5586 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    93.40%, min    93.40%,   3 3D sequences,     0 alignment sequences,  7971 random sequences,  526 random matches,  5 NTs, cWW-tSH-F
Group 199, HL_81100.2  has acceptance rules  -5.9180 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.9180 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    80.51%, min    80.51%,   3 3D sequences,     0 alignment sequences,  3930 random sequences,  766 random matches,  2 NTs, cWW
Group 200, HL_81205.3  has acceptance rules  -5.7721 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.7721 - AlignmentScore) +   3.0000 * CoreEdit <=  22.9065, method  8,TP   100.00%, TN    98.36%, min    98.36%,   2 3D sequences,     0 alignment sequences,    61 random sequences,    1 random matches, 14 NTs, cWW-cWW-tWH-F-tWH-F-F-F-F-F
Group 201, HL_81312.1  has acceptance rules  -6.2922 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.2922 - AlignmentScore) +   3.0000 * CoreEdit <=  18.5561, method  6,TP   100.00%, TN    95.51%, min    95.51%,   2 3D sequences,     0 alignment sequences,   980 random sequences,   44 random matches, 10 NTs, cWW-F-F-F-F-F-F-F-F-F
Group 202, HL_81538.2  has acceptance rules  -5.7878 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.7878 - AlignmentScore) +   3.0000 * CoreEdit <=  10.7108, method  6,TP   100.00%, TN    96.00%, min    96.00%,  16 3D sequences,     0 alignment sequences,  5843 random sequences,  234 random matches,  8 NTs, cWW-tSH-F-F-F-F
Group 203, HL_81545.2  has acceptance rules  -4.2796 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.2796 - AlignmentScore) +   3.0000 * CoreEdit <=  17.9293, method  6,TP   100.00%, TN    96.01%, min    96.01%,   7 3D sequences,     0 alignment sequences,  3109 random sequences,  124 random matches,  8 NTs, cWW-tWH-F-F-F-F
Group 204, HL_82710.2  has acceptance rules  -4.3329 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.3329 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    84.55%, min    84.55%,   4 3D sequences,     0 alignment sequences,  6034 random sequences,  932 random matches,  5 NTs, cWW-F-F-F
Group 205, HL_83632.1  has acceptance rules  -5.5779 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.5779 - AlignmentScore) +   3.0000 * CoreEdit <=  14.2316, method  6,TP   100.00%, TN    95.98%, min    95.98%,   6 3D sequences,     0 alignment sequences,  4581 random sequences,  184 random matches,  8 NTs, cWW-F-F-F-F-F-F
Group 206, HL_83808.4  has acceptance rules  -5.5686 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.5686 - AlignmentScore) +   3.0000 * CoreEdit <=  17.8376, method  6,TP   100.00%, TN    96.00%, min    96.00%,   3 3D sequences,     0 alignment sequences,  3322 random sequences,  133 random matches,  7 NTs, cWW-tWW-F-F-F
Group 207, HL_84299.4  has acceptance rules  -5.2909 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.2909 - AlignmentScore) +   3.0000 * CoreEdit <=  14.0118, method  6,TP   100.00%, TN    96.00%, min    96.00%,   9 3D sequences,     0 alignment sequences,  5356 random sequences,  214 random matches,  8 NTs, cWW-F-F-F-F-F-F
Group 208, HL_84847.1  has acceptance rules  -8.1397 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.1397 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0294, method  8,TP   100.00%, TN    97.93%, min    97.93%,   1 3D sequences,     0 alignment sequences,   193 random sequences,    4 random matches, 14 NTs, cWW-F-F-F-F-tWW-F-F-F-F-F-F
Group 209, HL_85367.2  has acceptance rules  -4.7419 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.7419 - AlignmentScore) +   3.0000 * CoreEdit <=  14.2472, method  6,TP   100.00%, TN    96.00%, min    96.00%,  11 3D sequences,     0 alignment sequences,  3778 random sequences,  151 random matches,  8 NTs, cWW-F-F-F-F-F-F
Group 210, HL_85434.1  has acceptance rules  -5.5869 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.5869 - AlignmentScore) +   3.0000 * CoreEdit <=  18.9079, method  6,TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences,  1697 random sequences,   68 random matches, 10 NTs, cWW-cWW-F-F-F-F-F-F
Group 211, HL_85461.1  has acceptance rules -14.9399 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-14.9399 - 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, 15 NTs, cWW-F-F-F-F-F-F-F-F-F-F-F-F-F
Group 212, HL_85993.1  has acceptance rules  -5.3471 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.3471 - AlignmentScore) +   3.0000 * CoreEdit <=  12.3927, method  6,TP   100.00%, TN    95.02%, min    95.02%,   1 3D sequences,     0 alignment sequences,  4478 random sequences,  223 random matches,  7 NTs, cWW-F-F-F-F-F
Group 213, HL_86012.1  has acceptance rules  -3.0954 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.0954 - AlignmentScore) +   3.0000 * CoreEdit <=  18.8810, method  6,TP   100.00%, TN    95.95%, min    95.95%,   2 3D sequences,     0 alignment sequences,  3656 random sequences,  148 random matches,  8 NTs, cWW-tWH-F-F-F-F
Group 214, HL_86109.1  has acceptance rules  -6.7310 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.7310 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.67%, min    97.67%,   3 3D sequences,     0 alignment sequences,   943 random sequences,   22 random matches, 12 NTs, cWW-F-tWH-F-F-F-F-F-F-F
Group 215, HL_86769.4  has acceptance rules  -8.0181 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.0181 - AlignmentScore) +   3.0000 * CoreEdit <=  10.8975, method  6,TP   100.00%, TN    96.01%, min    96.01%,   5 3D sequences,     0 alignment sequences,  8286 random sequences,  331 random matches,  7 NTs, cWW-cWW-cSH-F
Group 216, HL_86870.2  has acceptance rules  -5.3042 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.3042 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    85.49%, min    85.49%,   4 3D sequences,     0 alignment sequences,  7030 random sequences, 1020 random matches,  5 NTs, cWW-F-F-F
Group 217, HL_86883.1  has acceptance rules  -2.4589 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -2.4589 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    94.79%, min    94.79%,   2 3D sequences,     0 alignment sequences,  4071 random sequences,  212 random matches,  5 NTs, cWW-F-F-F
Group 218, HL_87463.1  has acceptance rules  -5.6113 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.6113 - AlignmentScore) +   3.0000 * CoreEdit <=  18.0784, method  6,TP   100.00%, TN    95.88%, min    95.88%,   1 3D sequences,     0 alignment sequences,  3426 random sequences,  141 random matches,  9 NTs, cWW-cWW-F-F-F-F-F
Group 219, HL_87553.1  has acceptance rules  -8.7270 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.7270 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    94.81%, min    94.81%,   7 3D sequences,     0 alignment sequences,  7502 random sequences,  389 random matches,  7 NTs, cWW-F-F-F-F-F
Group 220, HL_87954.2  has acceptance rules  -5.6698 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.6698 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    93.35%, min    93.35%,   7 3D sequences,     0 alignment sequences,  6388 random sequences,  425 random matches,  5 NTs, cWW-tSW-F
Group 221, HL_88205.2  has acceptance rules  -5.7168 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.7168 - AlignmentScore) +   3.0000 * CoreEdit <=  15.0111, method  6,TP   100.00%, TN    96.01%, min    96.01%,   7 3D sequences,     0 alignment sequences,  3583 random sequences,  143 random matches,  7 NTs, cWW-cWS-tSW-F-F
Group 222, HL_88364.2  has acceptance rules -10.2607 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-10.2607 - AlignmentScore) +   3.0000 * CoreEdit <=  19.8243, method  6,TP   100.00%, TN    96.72%, min    96.72%,   3 3D sequences,     0 alignment sequences,    61 random sequences,    2 random matches, 15 NTs, cWW-cWW-F-F-F-F-F-F-F-F-F-F-F
Group 223, HL_88558.1  has acceptance rules  -8.6616 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.6616 - AlignmentScore) +   3.0000 * CoreEdit <=  17.6937, method  6,TP   100.00%, TN    95.84%, min    95.84%,   1 3D sequences,     0 alignment sequences,  1634 random sequences,   68 random matches, 11 NTs, cWW-tSH-F-F-F-F-F-F-F
Group 224, HL_89199.2  has acceptance rules  -2.3710 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -2.3710 - AlignmentScore) +   3.0000 * CoreEdit <=  10.7958, method  6,TP   100.00%, TN    95.67%, min    95.67%,   5 3D sequences,     0 alignment sequences,  3768 random sequences,  163 random matches,  5 NTs, cWW-F-F-F
Group 225, HL_89346.1  has acceptance rules -17.8309 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-17.8309 - AlignmentScore) +   3.0000 * CoreEdit <=  25.0000, method  1,TP   100.00%, TN    50.00%, min    50.00%,   2 3D sequences,     0 alignment sequences,     2 random sequences,    1 random matches, 17 NTs, cWW-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F
Group 226, HL_89567.2  has acceptance rules  -3.9163 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.9163 - AlignmentScore) +   3.0000 * CoreEdit <=  12.5563, method  6,TP   100.00%, TN    95.97%, min    95.97%,   8 3D sequences,     0 alignment sequences,  5787 random sequences,  233 random matches,  5 NTs, cWW-F-F-F
Group 227, HL_89881.5  has acceptance rules  -4.8200 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.8200 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.88%, min    97.88%,   4 3D sequences,     0 alignment sequences,  1654 random sequences,   35 random matches, 10 NTs, cWW-tHW-F-F-F-F-F-F
Group 228, HL_89893.1  has acceptance rules  -4.6417 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.6417 - AlignmentScore) +   3.0000 * CoreEdit <=  12.2958, method  6,TP   100.00%, TN    95.80%, min    95.80%,   1 3D sequences,     0 alignment sequences,  6334 random sequences,  266 random matches,  6 NTs, cWW-F-F-F-F
Group 229, HL_90620.1  has acceptance rules  -7.0475 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.0475 - AlignmentScore) +   3.0000 * CoreEdit <=  17.3034, method  6,TP   100.00%, TN    96.00%, min    96.00%,   2 3D sequences,     0 alignment sequences,  1873 random sequences,   75 random matches, 11 NTs, cWW-F-F-F-F-cSW-cSH-F
Group 230, HL_91503.7  has acceptance rules  -6.9866 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.9866 - AlignmentScore) +   3.0000 * CoreEdit <=  18.0089, method  6,TP   100.00%, TN    96.01%, min    96.01%,   3 3D sequences,     0 alignment sequences,  2935 random sequences,  117 random matches,  9 NTs, cWW-F-F-F-F-F-F-F
Group 231, HL_91641.1  has acceptance rules -12.7400 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-12.7400 - AlignmentScore) +   3.0000 * CoreEdit <=  17.0988, method  6,TP   100.00%, TN    95.65%, min    95.65%,   1 3D sequences,     0 alignment sequences,    46 random sequences,    2 random matches, 16 NTs, cWW-F-F-F-F-F-F-F-F-cSW-F-F-F-F
Group 232, HL_91939.2  has acceptance rules  -8.0697 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.0697 - AlignmentScore) +   3.0000 * CoreEdit <=  19.3915, method  6,TP   100.00%, TN    96.00%, min    96.00%,   8 3D sequences,     0 alignment sequences,  2749 random sequences,  110 random matches, 11 NTs, cWW-tSH-tHH-tWW-F-F-F
Group 233, HL_92488.1  has acceptance rules -12.2192 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-12.2192 - AlignmentScore) +   3.0000 * CoreEdit <=  19.4007, method  6,TP   100.00%, TN    96.43%, min    96.43%,   1 3D sequences,     0 alignment sequences,    28 random sequences,    1 random matches, 13 NTs, cWW-cWW-F-cSS-F-F-F-F-F-F
Group 234, HL_93135.1  has acceptance rules  -8.5290 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.5290 - AlignmentScore) +   3.0000 * CoreEdit <=  16.4689, method  6,TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences,  1896 random sequences,   76 random matches,  8 NTs, cWW-F-F-F-F-F-F
Group 235, HL_93324.4  has acceptance rules  -7.3880 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.3880 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    93.51%, min    93.51%,  24 3D sequences,     0 alignment sequences,  6067 random sequences,  394 random matches,  8 NTs, cWW-F-F-F-F-F-F
Group 236, HL_93383.1  has acceptance rules  -3.4763 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.4763 - AlignmentScore) +   3.0000 * CoreEdit <=  17.9232, method  6,TP   100.00%, TN    96.02%, min    96.02%,   2 3D sequences,     0 alignment sequences,  1255 random sequences,   50 random matches,  9 NTs, cWW-cSH-F-F-F-F-F-F
Group 237, HL_93438.2  has acceptance rules  -7.2885 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.2885 - AlignmentScore) +   3.0000 * CoreEdit <=  16.6169, method  6,TP   100.00%, TN    96.01%, min    96.01%,   6 3D sequences,     0 alignment sequences,  5735 random sequences,  229 random matches, 10 NTs, cWW-F-F-F-F-F-F-F-F
Group 238, HL_93535.1  has acceptance rules  -6.0995 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.0995 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    85.65%, min    85.65%,   6 3D sequences,     0 alignment sequences,  6681 random sequences,  959 random matches,  6 NTs, cWW-F-F-F-F
Group 239, HL_93616.2  has acceptance rules  -5.8830 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -5.8830 - AlignmentScore) +   3.0000 * CoreEdit <=  20.0000, method  8,TP   100.00%, TN    97.52%, min    97.52%,   8 3D sequences,     0 alignment sequences,   927 random sequences,   23 random matches,  8 NTs, cWW-cWS-F-F-F-F
Group 240, HL_94376.1  has acceptance rules  -7.7719 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.7719 - AlignmentScore) +   3.0000 * CoreEdit <=  18.1608, method  6,TP   100.00%, TN    96.01%, min    96.01%,   3 3D sequences,     0 alignment sequences,  1629 random sequences,   65 random matches, 11 NTs, cWW-F-F-F-F-F-F-F-F-F
Group 241, HL_94980.1  has acceptance rules  -2.9167 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -2.9167 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    70.87%, min    70.87%,   1 3D sequences,     0 alignment sequences,  3406 random sequences,  992 random matches,  4 NTs, cWW-F-F
Group 242, HL_97733.1  has acceptance rules  -8.0884 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.0884 - AlignmentScore) +   3.0000 * CoreEdit <=  16.4738, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences,  2527 random sequences,  101 random matches,  8 NTs, cWW-F-F-F-cSH-F
Group 243, HL_97756.2  has acceptance rules  -4.7790 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.7790 - AlignmentScore) +   3.0000 * CoreEdit <=  25.0000, method  1,TP   100.00%, TN   100.00%, min   100.00%,   6 3D sequences,     0 alignment sequences,    19 random sequences,    0 random matches, 14 NTs, cWW-cSH-cWS-F-tSW-cSW-F-cWW-F-F-F
Group 244, HL_97917.2  has acceptance rules  -8.3964 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.3964 - AlignmentScore) +   3.0000 * CoreEdit <=   9.5000, method 11,TP   100.00%, TN    92.79%, min    92.79%,   3 3D sequences,     0 alignment sequences,  8116 random sequences,  585 random matches,  6 NTs, cWW-F-F-F-F
Group 245, HL_97983.1  has acceptance rules  -8.1869 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.1869 - AlignmentScore) +   3.0000 * CoreEdit <=  11.4748, method  6,TP   100.00%, TN    96.00%, min    96.00%,   1 3D sequences,     0 alignment sequences,  2423 random sequences,   97 random matches,  4 NTs, cWW-F-F
Group 246, HL_98252.1  has acceptance rules  -7.2938 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -7.2938 - AlignmentScore) +   3.0000 * CoreEdit <=  16.4785, method  6,TP   100.00%, TN    95.95%, min    95.95%,   1 3D sequences,     0 alignment sequences,  1704 random sequences,   69 random matches,  8 NTs, cWW-tWW-F-F-F-F
Group 247, HL_98864.1  has acceptance rules  -4.6293 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -4.6293 - AlignmentScore) +   3.0000 * CoreEdit <=  19.9385, method  6,TP   100.00%, TN    95.99%, min    95.99%,   4 3D sequences,     0 alignment sequences,  3513 random sequences,  141 random matches, 10 NTs, cWW-tWH-F-F-F-F-F-F
Group 248, HL_98870.1  has acceptance rules  -9.2985 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -9.2985 - AlignmentScore) +   3.0000 * CoreEdit <=  20.1634, method  8,TP   100.00%, TN    98.19%, min    98.19%,   2 3D sequences,     0 alignment sequences,   221 random sequences,    4 random matches, 11 NTs, cWW-tSH-tWW-F-F-F-F-F
Group 249, HL_99040.1  has acceptance rules  -3.2183 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -3.2183 - AlignmentScore) +   3.0000 * CoreEdit <=  11.3660, method  6,TP   100.00%, TN    95.96%, min    95.96%,   1 3D sequences,     0 alignment sequences,  3938 random sequences,  159 random matches,  6 NTs, F-F-F-F-F-F
Group 250, HL_99324.1  has acceptance rules -12.8649 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * (-12.8649 - AlignmentScore) +   3.0000 * CoreEdit <=  25.0000, method  1,TP   100.00%, TN    90.91%, min    90.91%,   2 3D sequences,     0 alignment sequences,    11 random sequences,    1 random matches, 17 NTs, cWW-F-F-F-F-F-F-F-F-F-F-F-F-F-F-F
Group 251, HL_99748.1  has acceptance rules  -6.7021 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -6.7021 - AlignmentScore) +   3.0000 * CoreEdit <=  12.6411, method  6,TP   100.00%, TN    95.99%, min    95.99%,   1 3D sequences,     0 alignment sequences,  6578 random sequences,  264 random matches,  6 NTs, cWW-F-F-cSH
Group 252, HL_99769.3  has acceptance rules  -8.7695 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.7695 - AlignmentScore) +   3.0000 * CoreEdit <=  18.2254, method  6,TP   100.00%, TN    96.00%, min    96.00%,   6 3D sequences,     0 alignment sequences,  3126 random sequences,  125 random matches,  8 NTs, cWW-cWW-F-F-F-F
Group 253, HL_99867.1  has acceptance rules  -8.5875 - AlignmentScore <=  20.0000, CoreEdit <= 5, and   1.0000 * ( -8.5875 - AlignmentScore) +   3.0000 * CoreEdit <=  14.1900, method  6,TP   100.00%, TN    95.94%, min    95.94%,   5 3D sequences,     0 alignment sequences,  3227 random sequences,  131 random matches, 10 NTs, cWW-F-F-F-F-F-F-F-F
