Skip to main content

Table 3 Comparison of generalized classification across sources

From: Learning virulent proteins from integrated query networks

Data source

Classification method

 

SVM(RBF)

Ridge regr.

k NN

AmiGO

0.894

0.907

0.867

BioCyc

0.698

0.687

0.679

CDD

0.729

0.760

0.755

GenNav

0.940

0.935

0.878

InterPro

0.846

0.804

0.832

Kegg

0.733

0.778

0.779

Kegg (pathways)

0.740

0.739

0.717

Pdb

0.740

0.737

0.710

TigrFam

0.688

0.702

0.704

  1. Results by source and method for predicting virulent and non-virulent bacterial proteins given AUC. The best performer, GenNav was run with a Gaussian kernel whose σ = 1.0 and regularization cost C = 1.0. For each method, the best performing classification approach is bolded.