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    Please use this identifier to cite or link to this item: http://ir.nhri.org.tw/handle/3990099045/1754


    Title: Bioinformatics models for predicting antigenic variants of influenza A/H3N2 virus
    Authors: Liao, YC;Lee, MS;Ko, CY;Hsiung, CA
    Contributors: Division of Biostatistics and Bioinformatics;Vaccine Research and Development Center
    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 19992004 (agreement rate 91.67). Twenty amino acid positions identified in our model contribute significantly to antigenic difference and are potential immunodominant positions.
    Keywords: Biochemical Research Methods;Biotechnology & Applied Microbiology;Computer Science, Interdisciplinary Applications;Mathematical & Computational Biology;Statistics & Probability
    Date: 2008-02-15
    Relation: Bioinformatics. 2008 Feb;24(4):505-512.
    Link to: http://dx.doi.org/10.1093/bioinformatics/btm638
    JIF/Ranking 2023: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=NHRI&SrcApp=NHRI_IR&KeyISSN=1367-4803&DestApp=IC2JCR
    Cited Times(WOS): https://www.webofscience.com/wos/woscc/full-record/WOS:000253246300009
    Cited Times(Scopus): http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=39149126039
    Appears in Collections:[熊昭] 期刊論文
    [廖玉潔] 期刊論文
    [李敏西] 期刊論文

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