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

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Abstract

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. © Oxford University Press 2004; All rights reserved.

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Bhasin, M., & Raghava, G. P. S. (2004). SVM based method for predicting HLA-DRB1*0401 binding peptides in an antigen sequence. Bioinformatics, 20(3), 421–423. https://doi.org/10.1093/bioinformatics/btg424

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