English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 55184/89457 (62%)
造访人次 : 10675545      在线人数 : 71
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜寻范围 查询小技巧:
  • 您可在西文检索词汇前后加上"双引号",以获取较精准的检索结果
  • 若欲以作者姓名搜寻,建议至进阶搜寻限定作者字段,可获得较完整数据
  • 进阶搜寻

    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/59913

    题名: Feature Selection for Identifying Protein Disordered Regions
    作者: Hsu, Hui-Huang;Hsieh, Cheng-Wei
    贡献者: 淡江大學資訊工程學系
    关键词: Disordered protein region;k-Medoids clustering;Feature selection;Proteomics
    日期: 2010-04
    上传时间: 2011-10-05 22:26:29 (UTC+8)
    出版者: Singapore: World Scientific Publishing Co. Pte. Ltd.
    摘要: Determining the structure of a protein is not an easy task, which usually involved a time-consuming and costly process in the web lab. Using computational methods to predict a protein's tertiary structure from its primary structure (the amino acid sequence) is desirable. Disordered regions are segments of a protein that do not have a fixed conformation, which makes the structure prediction harder. Also, these disordered regions are functionally important for a protein. In this research, we would like to identify such regions with a focus on selecting a proper feature set. Three feature selection methods, namely F-score, information gain (IG), and k-medoids clustering, are used for feature selection. The support vector machine (SVM) is then used for classification. The results show that the classification accuracy can be raised with a smaller feature set. The k-medoids clustering feature selection can reduce the number of features from 440 to 150 and improve the accuracy from 84.66 to 86.81% in five-fold cross validation. It also has a more stable performance than F-score and IG.
    關聯: Biomedical Engineering: Applications, Basis and Communications 22(2), pp.119-125
    DOI: 10.4015/S1016237210001839
    显示于类别:[資訊工程學系暨研究所] 期刊論文


    档案 描述 大小格式浏览次数
    1016-2372_22(2)p119-125.pdf299KbAdobe PDF235检视/开启



    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回馈