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    National Tsing Hua University Institutional Repository > 電機資訊學院 > 電機工程學系 > 期刊論文 >  Identifying regulatory targets of cell cycle transcription factors using gene expression and ChIP-chip data


    Please use this identifier to cite or link to this item: http://nthur.lib.nthu.edu.tw/dspace/handle/987654321/12007


    Title: Identifying regulatory targets of cell cycle transcription factors using gene expression and ChIP-chip data
    Authors: Wei-Sheng Wu
    Wen-Hsiung Li
    Bor-Sen Chen
    教師: 陳博現
    Date: 2007
    Publisher: BioMed Central
    Relation: BMC BIOINFORMATICS   Volume: 8 Article Number: 188   Published: JUN 8 2007
    Keywords: transcription factors
    TFs
    Temporal Relationship Identification Algorithm
    TRIA
    Abstract: Background
    ChIP-chip data, which indicate binding of transcription factors (TFs) to DNA regions in vivo, are widely used to reconstruct transcriptional regulatory networks. However, the binding of a TF to a gene does not necessarily imply regulation. Thus, it is important to develop methods to identify regulatory targets of TFs from ChIP-chip data.
    Results
    We developed a method, called Temporal Relationship Identification Algorithm (TRIA), which uses gene expression data to identify a TF's regulatory targets among its binding targets inferred from ChIP-chip data. We applied TRIA to yeast cell cycle microarray data and identified many plausible regulatory targets of cell cycle TFs. We validated our predictions by checking the enrichments for functional annotation and known cell cycle genes. Moreover, we showed that TRIA performs better than two published methods (MA-Network and MFA). It is known that co-regulated genes may not be co-expressed. TRIA has the ability to identify subsets of highly co-expressed genes among the regulatory targets of a TF. Different functional roles are found for different subsets, indicating the diverse functions a TF could have. Finally, for a control, we showed that TRIA also performs well for cell-cycle irrelevant TFs.
    Conclusion
    Finding the regulatory targets of TFs is important for understanding how cells change their transcription program to adapt to environmental stimuli. Our algorithm TRIA is helpful for achieving this purpose.
    Relation Link: http://www.biomedcentral.com/home/
    URI: http://nthur.lib.nthu.edu.tw/handle/987654321/12007
    Appears in Collections:[電機工程學系] 期刊論文
    [通訊工程研究所] 期刊論文

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