A hybrid model for prediction of peptide binding to MHC molecules

Ping Zhang, Vladimir Brusic, Kaye Basford

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages529-536
Number of pages8
Volume5506 LNCS
EditionPART 1
DOIs
Publication statusPublished - 2009
Externally publishedYes
Event15th International Conference on Neuro-Information Processing, ICONIP 2008 - Auckland, New Zealand
Duration: Nov 25 2008Nov 28 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume5506 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other15th International Conference on Neuro-Information Processing, ICONIP 2008
CountryNew Zealand
CityAuckland
Period11/25/0811/28/08

Fingerprint

Statistical tests
Hybrid Model
Peptides
Support vector machines
ROC Analysis
Molecules
Stabilized Methods
Preliminary Test
Prediction
Matrix Method
Statistical test
Support Vector Machine
Experiments
Experiment
Evidence

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Zhang, P., Brusic, V., & Basford, K. (2009). A hybrid model for prediction of peptide binding to MHC molecules. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (PART 1 ed., Vol. 5506 LNCS, pp. 529-536). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5506 LNCS, No. PART 1). https://doi.org/10.1007/978-3-642-02490-0_65

A hybrid model for prediction of peptide binding to MHC molecules. / Zhang, Ping; Brusic, Vladimir; Basford, Kaye.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5506 LNCS PART 1. ed. 2009. p. 529-536 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5506 LNCS, No. PART 1).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Zhang, P, Brusic, V & Basford, K 2009, A hybrid model for prediction of peptide binding to MHC molecules. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 1 edn, vol. 5506 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 5506 LNCS, pp. 529-536, 15th International Conference on Neuro-Information Processing, ICONIP 2008, Auckland, New Zealand, 11/25/08. https://doi.org/10.1007/978-3-642-02490-0_65
Zhang P, Brusic V, Basford K. A hybrid model for prediction of peptide binding to MHC molecules. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 1 ed. Vol. 5506 LNCS. 2009. p. 529-536. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). https://doi.org/10.1007/978-3-642-02490-0_65
Zhang, Ping ; Brusic, Vladimir ; Basford, Kaye. / A hybrid model for prediction of peptide binding to MHC molecules. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5506 LNCS PART 1. ed. 2009. pp. 529-536 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).
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