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Comparative Study
. 2004 Feb 12;20(3):421-3.
doi: 10.1093/bioinformatics/btg424. Epub 2004 Jan 22.

SVM based method for predicting HLA-DRB1*0401 binding peptides in an antigen sequence

Manoj Bhasin  1 , G P S Raghava
Affiliations
Comparative Study

SVM based method for predicting HLA-DRB1*0401 binding peptides in an antigen sequence

Manoj Bhasin et al. Bioinformatics. .

Abstract

Prediction of peptides binding with MHC class II allele HLA-DRB1(*)0401 can effectively reduce the number of experiments required for identifying helper T cell epitopes. This paper describes support vector machine (SVM) based method developed for identifying HLA-DRB1(*)0401 binding peptides in an antigenic sequence. SVM was trained and tested on large and clean data set consisting of 567 binders and equal number of non-binders. The accuracy of the method was 86% when evaluated through 5-fold cross-validation technique.

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