PFRMAT QA
TARGET C1907
AUTHOR MULTICOM-CONSTRUCT
METHOD Improving the estimation of protein model quality with deep networks for global QA
METHOD -------------
MODEL 2
QMODE 1
C1907TS359_1	0.567055
C1907TS369_1	0.566671
C1907TS405_4	0.564894
C1907TS210_3	0.560499
C1907TS210_4	0.559551
C1907TS299_4	0.558290
C1907TS102_2	0.556597
C1907TS196_1	0.556597
C1907TS131_1	0.556225
C1907TS131_2	0.556041
C1907TS299_3	0.555785
C1907TS131_5	0.555487
C1907TS131_3	0.554356
C1907TS210_1	0.554321
C1907TS131_4	0.553433
C1907TS299_2	0.553294
C1907TS299_1	0.552387
C1907TS405_2	0.552080
C1907TS152_3	0.552018
C1907TS210_2	0.551727
C1907TS299_5	0.551575
C1907TS438_5	0.551034
C1907TS405_1	0.550950
C1907TS438_3	0.545446
C1907TS044_1	0.545026
C1907TS301_1	0.545026
C1907TS405_3	0.543682
C1907TS247_1	0.538883
C1907TS247_2	0.537424
C1907TS438_2	0.536859
C1907TS152_2	0.536330
C1907TS152_1	0.535081
C1907TS413_5	0.533081
C1907TS413_1	0.532361
C1907TS413_3	0.529004
C1907TS247_5	0.527995
C1907TS413_2	0.526789
C1907TS413_4	0.526318
C1907TS152_4	0.526227
C1907TS438_1	0.525551
C1907TS438_4	0.524631
C1907TS309_1	0.524554
C1907TS414_4	0.523560
C1907TS247_4	0.522883
C1907TS414_1	0.522530
C1907TS247_3	0.520986
C1907TS211_4	0.519146
C1907TS347_1	0.518668
C1907TS066_1	0.517898
C1907TS152_5	0.516580
C1907TS414_5	0.516398
C1907TS210_5	0.513897
C1907TS414_3	0.511466
C1907TS414_2	0.509418
C1907TS405_5	0.508401
C1907TS240_1	0.499208
C1907TS309_2	0.496703
C1907TS228_3	0.496629
C1907TS158_4	0.496579
C1907TS278_4	0.496579
C1907TS240_4	0.493928
C1907TS369_5	0.493240
C1907TS389_3	0.492881
C1907TS240_2	0.492478
C1907TS240_3	0.491589
C1907TS240_5	0.491052
C1907TS073_2	0.489489
C1907TS073_5	0.488704
C1907TS228_4	0.488637
C1907TS073_1	0.488343
C1907TS228_2	0.488144
C1907TS228_1	0.487995
C1907TS228_5	0.487672
C1907TS211_1	0.487428
C1907TS073_4	0.487114
C1907TS182_3	0.486384
C1907TS182_1	0.486382
C1907TS087_1	0.485218
C1907TS073_3	0.482641
C1907TS211_3	0.482612
C1907TS273_3	0.480589
C1907TS389_2	0.480585
C1907TS345_5	0.480335
C1907TS087_2	0.480267
C1907TS389_1	0.480113
C1907TS369_3	0.479047
C1907TS309_3	0.477167
C1907TS123_1	0.477151
C1907TS010_4	0.474349
C1907TS211_5	0.472517
C1907TS389_4	0.471867
C1907TS349_1	0.471474
C1907TS349_5	0.470411
C1907TS273_1	0.469524
C1907TS273_2	0.469509
C1907TS369_4	0.468163
C1907TS258_2	0.468058
C1907TS278_5	0.467822
C1907TS158_5	0.467551
C1907TS258_5	0.467123
C1907TS123_3	0.466866
C1907TS010_5	0.464529
C1907TS349_2	0.462644
C1907TS258_1	0.461793
C1907TS010_2	0.461468
C1907TS369_2	0.460580
C1907TS258_4	0.459867
C1907TS087_4	0.459272
C1907TS010_1	0.459267
C1907TS456_1	0.459099
C1907TS456_3	0.457659
C1907TS345_1	0.455162
C1907TS230_5	0.454548
C1907TS230_1	0.454286
C1907TS123_4	0.454211
C1907TS123_5	0.454211
C1907TS215_1	0.451102
C1907TS404_5	0.451041
C1907TS211_2	0.450590
C1907TS158_1	0.450355
C1907TS278_1	0.450355
C1907TS456_4	0.449342
C1907TS404_3	0.449213
C1907TS230_2	0.448999
C1907TS258_3	0.448803
C1907TS404_2	0.446224
C1907TS158_3	0.445765
C1907TS278_3	0.445765
C1907TS456_5	0.444056
C1907TS404_1	0.444041
C1907TS067_1	0.443950
C1907TS067_4	0.443950
C1907TS010_3	0.443241
C1907TS404_4	0.440369
C1907TS345_2	0.438578
C1907TS456_2	0.438129
C1907TS215_5	0.438012
C1907TS179_1	0.436321
C1907TS200_1	0.436070
C1907TS102_1	0.434226
C1907TS103_2	0.434226
C1907TS230_4	0.430811
C1907TS054_3	0.429533
C1907TS182_2	0.428949
C1907TS067_2	0.428206
C1907TS067_5	0.428206
C1907TS345_3	0.426311
C1907TS067_3	0.425594
C1907TS182_4	0.424461
C1907TS158_2	0.423778
C1907TS278_2	0.423473
C1907TS182_5	0.416501
C1907TS349_3	0.416181
C1907TS054_2	0.415711
C1907TS345_4	0.414755
C1907TS389_5	0.414551
C1907TS349_4	0.412692
C1907TS215_4	0.410883
C1907TS215_2	0.410250
C1907TS003_1	0.408285
C1907TS123_2	0.406002
C1907TS003_3	0.405312
C1907TS215_3	0.405128
C1907TS054_1	0.398552
C1907TS230_3	0.397714
C1907TS054_4	0.388613
C1907TS087_3	0.377976
C1907TS054_5	0.373106
C1907TS003_2	0.370887
C1907TS273_4	0.355274
C1907TS490_1	0.343910
C1907TS273_5	0.332312
C1907TS087_5	0.276145
END



