From: Mining protein loops using a structural alphabet and statistical exceptionality
Loop words specificity | W set≥307 | UR w 7 | NS w 7 | OR w 7 | all loops4 | short loops5 | long loops6 |
---|---|---|---|---|---|---|---|
Long-loop-specific words | 758 (22.9%) | 23 | 475 | 260 | 23.2% | 12.2% | 33.9% |
Short-loop-specific words | 476 (14.4%) | 23 | 220 | 233 | 25.7% | 33.0 % | 18.6% |
Shared words 1 | 2076 (63.7%) | 120 | 1519 | 437 | 45.9% | 39.4% | 56.3% |
Flanking-region-specific words2 | 1879 (57.1%) | 102 | 1131 | 646 | 58.6% | 58.9% | 58.4% |
Flanking-region-unspecific words | 1431 (43.2%) | 64 | 1083 | 284 | 31.4% | 21.7% | 40.8% |
Loop-type-specific words3 | 2543 (78.8%) | 124 | 1605 | 814 | 66.3% | 64.3% | 68.2% |
Loop-type-unspecific words | 767 (23.2%) | 42 | 609 | 116 | 16.6% | 12.7% | 20.5% |