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Table 4 Disorder Prediction Performance at CASP8.

From: svm PRAT: SVM-based Protein Residue Annotation Toolkit

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
  1. * - 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.
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BMC Bioinformatics

ISSN: 1471-2105

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