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

Yu-Chieh Liao, Min-Shi Lee, Chin-Yu KoChao A. Hsiung
Bioinformatics, 卷.24(4), 頁碼.505-512
02/2008
PMID: 18187440

摘要

Clinical Biochemistry Computational Theory and Mathematics Computer Science Applications
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. © The Author 2008. Published by Oxford University Press. All rights reserved.

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