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Bioinformatics Advance Access originally published online on January 22, 2004
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Bioinformatics 20(3) © Oxford University Press 2004; all rights reserved.

Applications Note

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

Manoj Bhasin and G. P. S. Raghava *

Institute of Microbial Technology, Sector 39A, Chandigarh, India

Received on April 21, 2003 ; revised on June 18, 2003 ; accepted on August 8, 2003
Advance Access Publication January 22, 2004

Summary: 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.

Available: A web server HLA-DR4Pred based on above approach is available at http://www.imtech.res.in/raghava/hladr4pred/ and http://bioinformatics.uams.edu/mirror/hladr4pred/ (Mirror Site).

Supplementary information: http://www.imtech.res.in/raghava/hladr4pred/info.html

Contact: raghava{at}imtech.res.in

* To whom correspondence should be addressed.


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