SVM based method for predicting HLA-DRB1*0401 binding peptides in an antigen sequence.
other · Level V
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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.
Medical subject headings
- Artificial Intelligence
- HLA-DR Antigens
- Sequence Alignment
- Sequence Analysis, Protein