Method
|
ROC
|
Q_2
|
S
w
|
---|
MULTICOM
|
0.92
|
0.81
|
0.61
|
CBRC-DP_DR
|
0.91
|
0.81
|
0.62
|
GS-MetaServer2
|
0.91
|
0.83
|
0.66
|
McGuffin
|
0.91
|
0.82
|
0.64
|
DISOclust
|
0.91
|
0.82
|
0.64
|
GeneSilicoMeta
|
0.90
|
0.83
|
0.655
|
Poodle
|
0.90
|
0.80
|
0.61
|
CaspIta
|
0.89
|
0.78
|
0.571
|
fais-server
|
0.89
|
0.78
|
0.56
|
MULTICOM-CMFR
|
0.89
|
0.82
|
0.64
|
MARINER*
|
0.88
|
0.80
|
0.61
|
- * - MARINER used svm PRAT to train models for disorder prediction in participation at CASP8 using the
kernel with w = f = 11. We used the 723 sequences with disordered residues from the DisPro [7] dataset. The results are the official results from the CASP organizers and were presented by Dr. Joel Sussman at the Weizmann Institute of Science. Q2 denotes the 2-state accuracy for the prediction and S
w
is a weighted accuracy rewarding the prediction of disordered residue.