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Bioinformatics Advance Access published online on January 10, 2008
Bioinformatics, doi:10.1093/bioinformatics/btm638
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© The Author (2008). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Bioinformatics models for predicting antigenic variants of influenza A/H3N2 virus

Yu-Chieh Liao 1,#, Min-Shi Lee 2,#, Chin-Yu Ko 1 and Chao A. Hsiung 1,*

1Division of Biostatistics and Bioinformatics, 2Vaccine R&D Center, National Health Research Institutes, Zhunan 350, Taiwan

*To whom correspondence should be addressed. Dr. Chao A. Hsiung, E-mail: hsiung{at}nhri.org.tw


  Abstract

Motivation: Continual and accumulated mutations in hemagglutinin (HA) protein of influenza A virus generate novel antigenic strains that cause annual epidemics.

Results: We propose a model by incorporating scoring and regression methods to predict antigenic variants. Based on collected sequences of influenza A/H3N2 viruses isolated between 1971 and 2002, our model can be used to accurately predict the antigenic variants in 1999-2004 (agreement rate = 91.67%). Twenty amino acid positions identified in our model contribute significantly to antigenic difference and are potential immunodominant positions.

Contact: hsiung{at}nhri.org.tw

Supplemental information: The supplementary information includes 62 amino acid sequences of H3N2 viruses and 277 pair-wise antigenic distances.

Associate Editor: Dr. Limsoon Wong

#The first two authors contribute equally.

Received on July 20, 2007; revised on November 15, 2007; accepted on December 17, 2007

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[Abstract] [Full Text] [PDF]


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