Predictive vaccinology: Optimisation of predictions using support vector machine classifiers

Ivana Bozic, Guang Lan Zhang, Vladimir Brusic

Research output: Contribution to journalConference article

19 Citations (Scopus)

Abstract

Promiscuous human leukocyte antigen (HLA) binding peptides are ideal targets for vaccine development. Existing computational models for prediction of promiscuous peptides used hidden Markov models and artificial neural networks as prediction algorithms. We report a system based on support vector machines that outperforms previously published methods. Preliminary testing showed that it can predict peptides binding to HLA-A2 and -A3 supertype molecules with excellent accuracy, even for molecules where no binding data are currently available.

Original languageEnglish
Pages (from-to)375-381
Number of pages7
JournalLecture Notes in Computer Science
Volume3578
Publication statusPublished - Jan 1 2005
Event6th International Conference on Intelligent Data Engineering and Automated Learning - IDEAL 2005 - Brisbane, Australia
Duration: Jul 6 2005Jul 8 2005

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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