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Table 3 Comparison against different methods on SCOP 1.53 fold benchmark

From: A discriminative method for protein remote homology detection and fold recognition combining Top-n-grams and latent semantic analysis

Average ROC and ROC50 scores

Methods

ROC

ROC50

Source

SVM-Top-n-gram

   

n = 1

0.7309

0.319

 

n = 2

0.7929

0.490

 

n = 3

0.7740

0.314

 

SVM-Bprofile(Ph = 0.15)

0.7849

0.352

 

SVM-Top-n-gram – LSA(n = 2)

0.8121

0.552

 

SVM-Bprofile-LSA(Ph = 0.15)

0.8047

0.419

 

Profile(5,7.5)

0.9240

0.314

[10]

SW-PSSM(3.0,0.450,2.0)

0.9360

0.571

[10]

  1. SVM-Bprofile and SVM-Top-n-gram refer to the methods based on the two building blocks: binary profiles and Top-n-grams respectively. The methods with LSA suffix refer to the corresponding methods after latent semantic analysis. Source is the sources of results. The results of the methods based on binary profiles were obtained by running the implementation of our previous work.
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BMC Bioinformatics

ISSN: 1471-2105

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