# This file is the result of combining several RDB files, specifically # T0357.t06.dssp-ebghstl.rdb (weight 1.53986) # T0357.t06.stride-ebghtl.rdb (weight 1.24869) # T0357.t06.str2.rdb (weight 1.54758) # T0357.t06.alpha.rdb (weight 0.659012) # T0357.t04.dssp-ebghstl.rdb (weight 1.53986) # T0357.t04.stride-ebghtl.rdb (weight 1.24869) # T0357.t04.str2.rdb (weight 1.54758) # T0357.t04.alpha.rdb (weight 0.659012) # T0357.t2k.dssp-ebghstl.rdb (weight 1.53986) # T0357.t2k.stride-ebghtl.rdb (weight 1.24869) # T0357.t2k.str2.rdb (weight 1.54758) # T0357.t2k.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 T0357.t06.dssp-ebghstl.rdb # ============================================ # TARGET T0357 # Using neural net t06-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 T0357.t06-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 3.34133 # # ============================================ # Comments from T0357.t06.stride-ebghtl.rdb # ============================================ # TARGET T0357 # Using neural net t06-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 T0357.t06-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 3.34133 # # ============================================ # Comments from T0357.t06.str2.rdb # ============================================ # TARGET T0357 # Using neural net t06-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 T0357.t06-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 3.34133 # # ============================================ # Comments from T0357.t06.alpha.rdb # ============================================ # TARGET T0357 # Using neural net t06-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 T0357.t06-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 3.34133 # # ============================================ # Comments from T0357.t04.dssp-ebghstl.rdb # ============================================ # TARGET T0357 # Using neural net t06-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 T0357.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 3.34133 # # ============================================ # Comments from T0357.t04.stride-ebghtl.rdb # ============================================ # TARGET T0357 # 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 T0357.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 3.34133 # # ============================================ # Comments from T0357.t04.str2.rdb # ============================================ # TARGET T0357 # 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 T0357.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 3.34133 # # ============================================ # Comments from T0357.t04.alpha.rdb # ============================================ # TARGET T0357 # 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 T0357.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 3.34133 # # ============================================ # Comments from T0357.t2k.dssp-ebghstl.rdb # ============================================ # TARGET T0357 # Using neural net t2k-5740-IDaaHr-5-15-7-15-9-15-13-ebghstl-seeded.net # This is a 4-layer network, with # window units # 5 15 # 7 15 # 9 15 # 13 7 (1 EBGHSTL ) # The input amino acid frequencies were determined from # alignment T0357.t2k-thin90.a2m.gz # with weighted counts, using HenikoffWeight(-1 bits/column, 1) # Counts were regularized to probabilities using # /projects/compbio/lib/recode3.20comp # Total sequence weight for alignment was 9 # # ============================================ # Comments from T0357.t2k.stride-ebghtl.rdb # ============================================ # TARGET T0357 # Using neural net t2k-5651-IDaaHr-5-15-7-15-9-15-13-ebghtl-seeded.net # This is a 4-layer network, with # window units # 5 15 # 7 15 # 9 15 # 13 6 (1 EBGHTL ) # The input amino acid frequencies were determined from # alignment T0357.t2k-thin90.a2m.gz # with weighted counts, using HenikoffWeight(-1 bits/column, 1) # Counts were regularized to probabilities using # /projects/compbio/lib/recode3.20comp # Total sequence weight for alignment was 9 # # ============================================ # Comments from T0357.t2k.str2.rdb # ============================================ # TARGET T0357 # Using neural net t2k-5651-IDaaHr-5-15-7-15-9-15-13-str2-from-empty.net # This is a 4-layer network, with # window units # 5 15 # 7 15 # 9 15 # 13 13 (1 str2 ) # The input amino acid frequencies were determined from # alignment T0357.t2k-thin90.a2m.gz # with weighted counts, using HenikoffWeight(-1 bits/column, 1) # Counts were regularized to probabilities using # /projects/compbio/lib/recode3.20comp # Total sequence weight for alignment was 9 # # ============================================ # Comments from T0357.t2k.alpha.rdb # ============================================ # TARGET T0357 # Using neural net t2k-5651-IDaaHr-5-15-7-15-9-15-13-alpha-seeded.net # This is a 4-layer network, with # window units # 5 15 # 7 15 # 9 15 # 13 11 (1 ABCDEFGHIST ) # The input amino acid frequencies were determined from # alignment T0357.t2k-thin90.a2m.gz # with weighted counts, using HenikoffWeight(-1 bits/column, 1) # Counts were regularized to probabilities using # /projects/compbio/lib/recode3.20comp # Total sequence weight for alignment was 9 # # ============================================ Pos AA E H C 10N 1S 5N 5N 5N 1 P 0.0937 0.0240 0.8823 2 K 0.3198 0.0579 0.6223 3 A 0.6238 0.0458 0.3304 4 I 0.7773 0.0414 0.1813 5 I 0.7576 0.0363 0.2060 6 N 0.4788 0.0524 0.4689 7 K 0.1579 0.1425 0.6996 8 K 0.0651 0.1635 0.7714 9 T 0.1098 0.1745 0.7156 10 E 0.1026 0.1355 0.7619 11 T 0.1665 0.2278 0.6057 12 I 0.4010 0.3662 0.2327 13 I 0.4585 0.4030 0.1386 14 A 0.5118 0.3847 0.1035 15 V 0.4583 0.4123 0.1294 16 G 0.4714 0.3769 0.1517 17 A 0.4672 0.3977 0.1351 18 A 0.3988 0.4189 0.1823 19 M 0.3113 0.3543 0.3344 20 A 0.1813 0.1923 0.6264 21 E 0.1430 0.0921 0.7649 22 I 0.2156 0.0336 0.7507 23 P 0.2834 0.0387 0.6780 24 L 0.2534 0.1671 0.5796 25 V 0.3285 0.1312 0.5403 26 E 0.2122 0.1651 0.6227 27 V 0.1273 0.2257 0.6470 28 R 0.1056 0.2310 0.6634 29 D 0.1301 0.1890 0.6809 30 E 0.1359 0.2206 0.6435 31 K 0.1497 0.1569 0.6934 32 F 0.0697 0.6093 0.3210 33 F 0.1032 0.7038 0.1930 34 E 0.1310 0.7105 0.1585 35 A 0.1910 0.6220 0.1870 36 V 0.2809 0.4277 0.2914 37 K 0.2316 0.3164 0.4520 38 T 0.1342 0.1165 0.7493 39 G 0.0538 0.0418 0.9044 40 D 0.1891 0.0170 0.7939 41 R 0.7957 0.0042 0.2000 42 V 0.9046 0.0038 0.0916 43 V 0.9207 0.0034 0.0759 44 V 0.8933 0.0054 0.1013 45 N 0.7477 0.0059 0.2464 46 A 0.0792 0.1091 0.8117 47 D 0.0439 0.1160 0.8401 48 E 0.1396 0.0596 0.8008 49 G 0.2675 0.0367 0.6958 50 Y 0.7752 0.0190 0.2058 51 V 0.8870 0.0100 0.1030 52 E 0.8659 0.0156 0.1185 53 L 0.8059 0.0210 0.1730 54 I 0.4527 0.0417 0.5056 55 E 0.0618 0.0349 0.9033