USING COMPUTERS TO ANALYZE TRANSCRIPTION FACTOR NETWORKS

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The goal of this research proposal is to develop and implement new computational methods that describe transcription factor networks, the "hardwired" genetic signals that control many developmental and other cellular processes. The method uses large gene expression data sets and raw sequence of regulatory regions to correlate expression of a transcription factor with a potential binding sequence, that is, any short motif in the regulatory regions of expressed genes. The first stage of the project calls for developing the algorithm using existing microarray expression data sets and raw upstream sequence. The second part of the proposal entails adapting the technique to a multicellular organism and developing molecular techniques to gather cell-type specific expression data. Transcription factors have been implicated in human genetic disease (e.g. retinoblastoma). Understanding transcription factor networks has great potential for treatment of diseases and developmental defects.