# This file is the result of combining several RDB files, specifically # miniAGRP.t04.dssp-ebghstl.rdb (weight 1.53986) # miniAGRP.t04.stride-ebghtl.rdb (weight 1.24869) # miniAGRP.t04.str2.rdb (weight 1.54758) # miniAGRP.t04.alpha.rdb (weight 0.659012) # These files were combined by translating their predictions into EHL # predictions with tables generated by compare-real, and then combining # those predictions with weights proportional to their mutual information # with the EHL alphabet. The comments from the individual files follow. # # Comments from miniAGRP.t04.dssp-ebghstl.rdb # ============================================ # TARGET miniAGRP # Using neural net t04-2621-IDGaaH13-3-13-7-13-9-13-11-ebghstl-dssp-seeded.net # This is a 4-layer network, with # window units # 3 13 # 7 13 # 9 13 # 11 7 (1 EBGHSTL ) # The input amino acid frequencies were determined from # alignment miniAGRP.t04-thin90.a2m.gz # with weighted counts, using HenikoffWeight(1.3 bits/column, 1) # The weighting was determined by the posterior distribution # after regularizing with /projects/compbio/lib/recode3.20comp. # Counts were regularized to probabilities using # /projects/compbio/lib/recode3.20comp # Total sequence weight for alignment was 1.85826 # # ============================================ # Comments from miniAGRP.t04.stride-ebghtl.rdb # ============================================ # TARGET miniAGRP # Using neural net t04-2621-IDGaaH13-3-13-7-13-9-13-11-ebghtl-stride-seeded.net # This is a 4-layer network, with # window units # 3 13 # 7 13 # 9 13 # 11 6 (1 EBGHTL ) # The input amino acid frequencies were determined from # alignment miniAGRP.t04-thin90.a2m.gz # with weighted counts, using HenikoffWeight(1.3 bits/column, 1) # The weighting was determined by the posterior distribution # after regularizing with /projects/compbio/lib/recode3.20comp. # Counts were regularized to probabilities using # /projects/compbio/lib/recode3.20comp # Total sequence weight for alignment was 1.85826 # # ============================================ # Comments from miniAGRP.t04.str2.rdb # ============================================ # TARGET miniAGRP # Using neural net t04-2621-IDGaaH13-3-13-7-13-9-13-11-str2-seeded.net # This is a 4-layer network, with # window units # 3 13 # 7 13 # 9 13 # 11 13 (1 str2 ) # The input amino acid frequencies were determined from # alignment miniAGRP.t04-thin90.a2m.gz # with weighted counts, using HenikoffWeight(1.3 bits/column, 1) # The weighting was determined by the posterior distribution # after regularizing with /projects/compbio/lib/recode3.20comp. # Counts were regularized to probabilities using # /projects/compbio/lib/recode3.20comp # Total sequence weight for alignment was 1.85826 # # ============================================ # Comments from miniAGRP.t04.alpha.rdb # ============================================ # TARGET miniAGRP # Using neural net t04-2621-IDGaaH13-3-13-7-13-9-13-11-alpha-seeded.net # This is a 4-layer network, with # window units # 3 13 # 7 13 # 9 13 # 11 11 (1 ABCDEFGHIST ) # The input amino acid frequencies were determined from # alignment miniAGRP.t04-thin90.a2m.gz # with weighted counts, using HenikoffWeight(1.3 bits/column, 1) # The weighting was determined by the posterior distribution # after regularizing with /projects/compbio/lib/recode3.20comp. # Counts were regularized to probabilities using # /projects/compbio/lib/recode3.20comp # Total sequence weight for alignment was 1.85826 # # ============================================ Pos AA E H C 10N 1S 5N 5N 5N 1 C 0.1387 0.0474 0.8139 2 V 0.3014 0.0512 0.6473 3 R 0.3378 0.0773 0.5849 4 L 0.2680 0.2605 0.4714 5 H 0.2382 0.3260 0.4358 6 E 0.1884 0.4305 0.3812 7 S 0.1250 0.4019 0.4731 8 C 0.1434 0.3657 0.4909 9 L 0.1066 0.2340 0.6594 10 G 0.0751 0.1322 0.7926 11 Q 0.1769 0.0724 0.7508 12 Q 0.2848 0.0471 0.6682 13 V 0.2019 0.0250 0.7730 14 P 0.1800 0.0387 0.7813 15 C 0.1628 0.0851 0.7521 16 C 0.1701 0.0622 0.7677 17 D 0.0989 0.0347 0.8664 18 P 0.0307 0.3273 0.6419 19 A 0.0418 0.3294 0.6288 20 A 0.0624 0.4033 0.5343 21 T 0.1687 0.4010 0.4303 22 C 0.2701 0.4135 0.3164 23 Y 0.2820 0.5204 0.1976 24 C 0.2270 0.5758 0.1972 25 R 0.1869 0.6104 0.2027 26 F 0.1627 0.6500 0.1874 27 F 0.1779 0.6173 0.2048 28 N 0.1644 0.5738 0.2618 29 A 0.1896 0.5669 0.2435 30 F 0.2867 0.4761 0.2372 31 C 0.4107 0.2804 0.3089 32 Y 0.4033 0.1831 0.4136 33 C 0.2812 0.0910 0.6279 34 R 0.0999 0.0621 0.8380