Predictive vaccinology: Optimisation of predictions using support vector machine classifiers

Ivana Bozic, Guang Lan Zhang, Vladimir Brusic

Research output: Journal PublicationConference articlepeer-review

21 Citations (Scopus)


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
Publication statusPublished - 2005
Externally publishedYes
Event6th International Conference on Intelligent Data Engineering and Automated Learning - IDEAL 2005 - Brisbane, Australia
Duration: 6 Jul 20058 Jul 2005

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


Dive into the research topics of 'Predictive vaccinology: Optimisation of predictions using support vector machine classifiers'. Together they form a unique fingerprint.

Cite this