PFRMAT DR
TARGET MAP4K4_351-494
AUTHOR IntFOLD6
METHOD IntFOLD6-DR: The DISOclust method is based on the analysis of the errors in the IntFOLD6-TS 3D models: McGuffin, L. J. (2008) Intrinsic disorder prediction from the analysis of multiple protein fold recognition models. Bioinformatics, 24, 586-587.
MODEL  1
T D 0.607
L D 0.556
R O 0.496
R O 0.452
D O 0.445
F O 0.454
L O 0.452
R D 0.505
L O 0.497
Q O 0.469
Q O 0.450
E O 0.492
N D 0.563
K D 0.571
E D 0.603
R D 0.616
S D 0.636
E D 0.613
A D 0.602
L D 0.662
R D 0.669
R D 0.719
Q D 0.729
Q D 0.702
L D 0.682
L D 0.685
Q D 0.664
E D 0.625
Q D 0.629
Q D 0.654
L D 0.611
R D 0.592
E D 0.629
Q D 0.553
E O 0.488
E O 0.458
Y O 0.454
K O 0.411
R O 0.383
Q O 0.392
L O 0.368
L O 0.363
A O 0.362
E O 0.370
R O 0.353
Q O 0.357
K O 0.362
R O 0.372
I O 0.384
E O 0.391
Q O 0.397
Q O 0.383
K O 0.366
E O 0.372
Q O 0.384
R O 0.370
R O 0.373
R O 0.381
L O 0.384
E O 0.419
E O 0.411
Q O 0.398
Q O 0.379
R O 0.389
R O 0.366
E O 0.357
R O 0.360
E O 0.366
A O 0.372
R O 0.393
R O 0.401
Q O 0.406
Q O 0.413
E O 0.429
R O 0.474
E D 0.510
Q D 0.523
R D 0.559
R D 0.539
R D 0.549
E D 0.547
Q D 0.573
E D 0.570
E D 0.583
K D 0.586
R D 0.556
R D 0.560
L D 0.601
E D 0.620
E D 0.630
L D 0.606
E D 0.622
R D 0.596
R D 0.628
R D 0.639
K D 0.627
E D 0.658
E D 0.660
E D 0.661
E D 0.641
R D 0.673
R D 0.707
R D 0.702
A D 0.733
E D 0.736
D D 0.707
E D 0.643
K D 0.647
R D 0.626
R D 0.581
V D 0.597
E D 0.616
R D 0.645
E D 0.592
Q D 0.669
E D 0.684
Y D 0.695
I D 0.690
R D 0.648
R D 0.670
Q D 0.655
L D 0.673
E D 0.639
E D 0.640
E D 0.634
Q D 0.637
R D 0.626
H D 0.632
L D 0.641
E D 0.601
I D 0.598
L D 0.584
Q D 0.587
Q D 0.645
Q D 0.623
L D 0.614
L D 0.576
Q D 0.546
E D 0.531
Q D 0.524
A D 0.592
M D 0.591
L D 0.599
L D 0.607
END