基因微陣列的出現使得上萬的基因表現得以同時被測量，此科技幫助達成生物計算分析：轉錄因子與表現變動的基因之互動關係。由於實驗證明許多不同轉錄因子會產生互動，且對基因調控有相輔相成之作用，而過去從微陣列數據裡只找單個首要轉錄因子的方法，很明顯地不足以解釋錯綜複雜之基因調控。

所以本論文中運用轉錄因子相對的DNA結合區之位置與轉錄因子兩兩相互關係作更深入的分析，進而對基因表現之變動達到更深層的理解。換言之，在表現變動的基因群裡，試圖找出較能解釋所控制的基因表現之轉錄因子、轉錄因子之相互關係或特定DNA結合區之位置。

Emerging of microarray experiments have rendered simultaneous screenings of thousands of gene expressions possible, and subsequent analyses of transcription factors that highly correlate with differentially expressed genes can be conducted to determine the likely mechanism of gene regulation. Since transcription factors have been proven to work cooperatively with one another as composite elements by a growing body of evidence, previous efforts in identifying only one transcription factor for each experiment are clearly insufficient to decipher the complex underlying mechanism of expression changes.

Therefore, the attempt here incorporates the analysis of TF binding positions and focuses on detecting TF pairs from genes with altered expressions. In combination of microarray and promoter binding site analysis, we predict pairs of transcription factors that mostly likely contribute to the regulated transcription of differentially expressed genes. The Expectation Maximization clustering of the TF binding positions is made available in order to detect a pattern in specific TF binding and predict the role it might play in regulation.

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