Table 4

Disorder Prediction Performance at CASP8.

Method

ROC

Q_2

Sw


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 svmPRAT 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 Sw is a weighted accuracy rewarding the prediction of disordered residue.

Rangwala et al. BMC Bioinformatics 2009 10:439   doi:10.1186/1471-2105-10-439

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