PFRMAT QA
TARGET C1910
AUTHOR MULTICOM-CONSTRUCT
METHOD Improving the estimation of protein model quality with deep networks for global QA
METHOD -------------
MODEL 2
QMODE 1
C1910TS278_5	0.717358
C1910TS299_5	0.717358
C1910TS278_4	0.717309
C1910TS299_4	0.717309
C1910TS278_3	0.716560
C1910TS299_3	0.716369
C1910TS278_2	0.714634
C1910TS299_2	0.714634
C1910TS210_1	0.714488
C1910TS414_2	0.712490
C1910TS278_1	0.712349
C1910TS299_1	0.712349
C1910TS210_4	0.707845
C1910TS210_5	0.706817
C1910TS413_3	0.706569
C1910TS413_1	0.703670
C1910TS405_3	0.702404
C1910TS369_2	0.701950
C1910TS369_3	0.701262
C1910TS369_4	0.699565
C1910TS405_2	0.699403
C1910TS210_2	0.699048
C1910TS210_3	0.699003
C1910TS309_1	0.698714
C1910TS405_4	0.697538
C1910TS369_1	0.697211
C1910TS359_1	0.695221
C1910TS438_2	0.695156
C1910TS405_1	0.694107
C1910TS309_5	0.693627
C1910TS413_4	0.693500
C1910TS413_2	0.689508
C1910TS414_3	0.689432
C1910TS438_3	0.687632
C1910TS196_1	0.686289
C1910TS152_1	0.685725
C1910TS131_3	0.685719
C1910TS131_4	0.685425
C1910TS131_1	0.682409
C1910TS131_2	0.682176
C1910TS247_2	0.681241
C1910TS131_5	0.680569
C1910TS405_5	0.679267
C1910TS414_1	0.675717
C1910TS413_5	0.674040
C1910TS414_4	0.673619
C1910TS414_5	0.673573
C1910TS152_2	0.672813
C1910TS369_5	0.671149
C1910TS211_1	0.670247
C1910TS309_2	0.669858
C1910TS044_1	0.669517
C1910TS301_1	0.669517
C1910TS152_3	0.665605
C1910TS054_3	0.663043
C1910TS054_5	0.661707
C1910TS438_1	0.660291
C1910TS247_4	0.658827
C1910TS087_3	0.657616
C1910TS247_3	0.656906
C1910TS309_4	0.656689
C1910TS087_1	0.656629
C1910TS247_5	0.654902
C1910TS349_4	0.653459
C1910TS438_4	0.653013
C1910TS349_1	0.652020
C1910TS349_5	0.651751
C1910TS349_3	0.651708
C1910TS349_2	0.651270
C1910TS066_1	0.650868
C1910TS182_1	0.650842
C1910TS054_4	0.650131
C1910TS247_1	0.649868
C1910TS054_1	0.649772
C1910TS404_2	0.648534
C1910TS347_1	0.647012
C1910TS404_3	0.647006
C1910TS404_1	0.646998
C1910TS404_4	0.643013
C1910TS438_5	0.640459
C1910TS389_2	0.635937
C1910TS389_1	0.634107
C1910TS152_4	0.633531
C1910TS182_3	0.633457
C1910TS309_3	0.631523
C1910TS240_5	0.630919
C1910TS054_2	0.630595
C1910TS389_3	0.629897
C1910TS240_2	0.629615
C1910TS240_1	0.629357
C1910TS240_3	0.628208
C1910TS215_1	0.624306
C1910TS182_4	0.623869
C1910TS230_2	0.622944
C1910TS240_4	0.622579
C1910TS182_2	0.621557
C1910TS228_3	0.620492
C1910TS404_5	0.617480
C1910TS389_4	0.615733
C1910TS230_3	0.611403
C1910TS182_5	0.609907
C1910TS389_5	0.607126
C1910TS179_1	0.603497
C1910TS230_1	0.603334
C1910TS211_2	0.596660
C1910TS158_5	0.595846
C1910TS258_5	0.592796
C1910TS158_4	0.588141
C1910TS003_1	0.585402
C1910TS258_2	0.580894
C1910TS123_4	0.580282
C1910TS123_5	0.580282
C1910TS258_3	0.575220
C1910TS158_1	0.574941
C1910TS158_2	0.571790
C1910TS123_3	0.569923
C1910TS215_5	0.567827
C1910TS228_2	0.563357
C1910TS258_1	0.561946
C1910TS228_4	0.559801
C1910TS228_5	0.559322
C1910TS228_1	0.558327
C1910TS123_1	0.557162
C1910TS123_2	0.557162
C1910TS258_4	0.556969
C1910TS102_1	0.553261
C1910TS103_1	0.552923
C1910TS158_3	0.551842
C1910TS067_3	0.551251
C1910TS067_4	0.546971
C1910TS067_1	0.546812
C1910TS003_3	0.539533
C1910TS003_2	0.538425
C1910TS067_2	0.536462
C1910TS067_5	0.536462
C1910TS152_5	0.528055
C1910TS230_4	0.527961
C1910TS215_4	0.520489
C1910TS273_5	0.507804
C1910TS273_1	0.495693
C1910TS211_5	0.495131
C1910TS230_5	0.493407
C1910TS211_3	0.492544
C1910TS211_4	0.491731
C1910TS087_2	0.491527
C1910TS273_4	0.491347
C1910TS215_3	0.490651
C1910TS345_3	0.479251
C1910TS010_1	0.477435
C1910TS345_2	0.476745
C1910TS273_2	0.476605
C1910TS345_4	0.476383
C1910TS215_2	0.473124
C1910TS010_4	0.465924
C1910TS345_5	0.463309
C1910TS345_1	0.457952
C1910TS073_4	0.455913
C1910TS073_2	0.434362
C1910TS073_1	0.421509
C1910TS073_3	0.421201
C1910TS073_5	0.418731
C1910TS010_2	0.415730
C1910TS273_3	0.403717
C1910TS010_5	0.400182
C1910TS010_3	0.353853
END



