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    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/2642


    Title: Immunogenicity Prediction with Neural Network and Support Vector Machine
    Authors: Wan Chen Lan
    Contributors: Department of Bioinformatics
    Keywords: Immunogenicity Prediction
    Date: 2009
    Issue Date: 2009-11-06 14:33:17 (UTC+0)
    Publisher: Asia University
    Abstract: Epitope, also named as antigenic determinant is the region that is recognized by antibody. In general, the length of the region in a protein sequence is about 6 to 8 amino acids. It is located on the exposed part in the protein structure for the reason that binding to the antibody. T cell epitopes are bound to MHC I/II on the surface of antigen-presenting cell and also bound to the receptor of T cell in the same time. One antigen could contain many epitopes, the number of epitopes increase with the increasing of the structural complexity and the molecular weight in the antigen.
    Epitope prediction is one of the important issues in vaccine design. In this study, we applied neural network and support vector machine to predict epitomes based on physiochemical properties of amino acids.
    Appears in Collections:[生物資訊與醫學工程學系 ] 博碩士論文

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