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    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/8118


    Title: A data mining method to predict transcriptional regulatory sites based on differentially expressed genes in human genome
    Authors: H. D. Huang;H. L. Chang;T. S. Tsou;B. J. Liu;J. T. Horng
    Contributors: Department of Bioinformatics
    Keywords: regulatory site;transcription factor;data mining;gene expression;UniGene;EST
    Date: 2003-11
    Issue Date: 2010-03-19 16:24:22 (UTC+8)
    Publisher: Asia University
    Abstract: Very large-scale gene expression analysis, i.e., UniGene and dbEST, is provided to
    find those genes with significantly differential expression in specific tissues. The differentially
    expressed genes in a specific tissue are potentially regulated concurrently by a
    combination of transcription factors. This study attempts to mine putative binding sites
    on how combinations of the known regulatory sites homologs and over-represented repetitive
    elements are distributed in the promoter regions of considered groups of differentially
    expressed genes. We propose a data mining approach to statistically discover the
    significantly tissue-specific combinations of known site homologs and over-represented
    repetitive sequences, which are distributed in the promoter regions of differentially gene
    groups. The association rules mined would facilitate to predict putative regulatory elements
    and identify genes potentially co-regulated by the putative regulatory elements.
    Relation: Journal of Information Science and Engineering 19 (6): 923-942
    Appears in Collections:[生物資訊與醫學工程學系 ] 期刊論文

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