Skip to main content
Presentation
A hybrid model for prediction of peptide binding to MHC molecules
Paper presented at the 15th International Conference on Neuro-Information Processing (ICONIP 2008) (2008)
  • P. Zhang
  • V. Brusic
  • K. Basford
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.

© Copyright Springer-Verlag Berlin Heidelberg, 2009

Access the published version at www.springerlink.com/.

Keywords
  • hybrid model,
  • peptide binding,
  • MHC molecules
Publication Date
November 28, 2008
Citation Information
P. Zhang, V. Brusic and K. Basford. "A hybrid model for prediction of peptide binding to MHC molecules" Paper presented at the 15th International Conference on Neuro-Information Processing (ICONIP 2008) (2008)
Available at: http://works.bepress.com/ping_zhang/11/