A hybrid model for prediction of peptide binding to MHC molecules

Abstract

We propose a hybrid classification system for predicting peptide binding to major histocompatibility complex (MHC) molecules. This system combines Support Vector Machine (SVM) and Stabilized Matrix Method (SMM). Its performance was assessed using ROC analysis, and compared with the individual component methods using statistical tests. The preliminary test on four HLA alleles provided encouraging evidence for the hybrid model. The datasets used for the experiments are publicly accessible and have been benchmarked by other researchers. © 2009 Springer Berlin Heidelberg.