• 我要登录|
  • 免费注册
    |
  • 我的丁香通
    • 企业机构:
    • 成为企业机构
    • 个人用户:
    • 个人中心
  • 移动端
    移动端
丁香通 logo丁香实验_LOGO
搜实验

    大家都在搜

      大家都在搜

        0 人通过求购买到了急需的产品
        免费发布求购
        发布求购
        点赞
        收藏
        wx-share
        分享

        Bioinformatics: Microarray Data Clustering and Functional Classification

        互联网

        540
        The human genome project has opened up a new page in scientific history. To this end, a variety of techniques such as microarray has evolved to monitor the transcript abundance for all of the organism’s genes rapidly and efficiently. Behind the massive numbers produced by these techniques, which amount to hundreds of data points for thousands or tens of thousands of genes, there hides an immense amount of biological information. The importance of microarray data analysis lies in presenting functional annotations and classifications. The process of the functional classifications is conducted as follows. The first step is to cluster gene expression data. Cluster 3.0 and Java Treeview are widely used open-source programs to group together genes with similar pattern of expressions, and to provide a computational and graphical environment for analyzing data from DNA microarray experiments, or other genomic datasets. Clustered genes can later be decoded by Bulk Gene Searching Systems in Java (BGSSJ). BGSSJ is an XML-based Java application that systemizes lists of interesting genes and proteins for biological interpretation in the context of the gene ontology. Gene ontology gathers information for molecular function, biological processes, and cellular components with a number of different organisms. In this chapter, in terms of how to use Cluster 3.0 and Java Treeview for microarray data clustering, and BGSSJ for functional classification are explained in detail.
        ad image
        提问
        扫一扫
        丁香实验小程序二维码
        实验小助手
        丁香实验公众号二维码
        扫码领资料
        反馈
        TOP
        打开小程序