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    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/16651

    Title: Theoretical Assessment of Immunogenicity Variation on The HA protein of H2N2 influenza virus by using fuzzy integral and SVM classifier.
    Authors: 劉湘川;Liu, Hsiang-Chuan;張培均;Chang, Pei-Chun
    Contributors: 生物與醫學資訊學系
    Keywords: Hemagglutininj epitopej influenza immunogenicityj fuzzy measurej fuzzy integral;SVM
    Machine Learning and Cybernetics (ICMLC), 2011 International Conference on (Volume:2 )
    Date: 2011
    Issue Date: 2012-11-23 17:15:31 (UTC+8)
    Abstract: "Hemagglutinin (HA) is the surface protein of influenza
    viruses, which is known to play important role in the infection
    process. It is the antigen that inducing immune responses and
    currently be used as the influenza vaccine potency marker.
    Epitope are some segments in the antigen which could be
    recognized by the immune system specifically and induce
    immune response. The T-cell epitopes of protein antigens are
    some peptides that presented on the cell surface by MHC
    molecules via the MHC class I pathway or the MHC class II
    pathway. The antigen presentation mechanisms are different in
    these two pathways. The MHC class I pathway is used to present
    endogeneous antigens to cytotoxic T cell, while the MHC class II
    pathway is used to present the extracellular antigens to helper T
    cell. The epitope with strong immune response is good target for
    vaccine design. Recently, the type of H2N2 influenza has a
    tendency towards popular again. To understand the
    immunogenicity variation among the HA proteins of H2N2
    influenza for the past decade is important for deciphering the
    infection tendency. It is also a clue to design effective vaccine in
    Fuzzy measure considers a series of special classes of
    measures and defined by a special property, respectively. The
    concept of fuzzy measure theory was introduced by Choquet in
    1953 and independently defined by Sugeno in 1974 in the
    context of fuzzy integrals. The Choquet integral is a fuzzy
    integral based on any fuzzy measure that provides a
    computational scheme for information aggregation.
    In this study, we proposed a novel algorithm with high
    accuracy in immunogenicity prediction based on fuzzy measure
    and SVM classifier. Accordingly, we applied this prediction
    method to assess the immunogenicity variation on the HA
    protein of H2N2 influenza virus for the past three decades. The
    results show that the immunogenicity strength decreased for
    MH C class II response that implied the increasing tendency of
    influenza outbreak by H2N2 virus. "
    Relation: International Conference on Machine Learning and Cybernetics
    Appears in Collections:[生物資訊與醫學工程學系 ] 期刊論文

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