A combined experimental and computational approach.. (TRANSCRIPTION_REG)
A combined experimental and computational approach for quantitative and mechanistic understanding of transcriptional regulation
Start date: Jul 1, 2008,
End date: Jun 30, 2013
"The complex functions of a living cell are carried out through the coordinated activity of many genes. Since transcription is a key step in establishing such coordinated activity, much effort was devoted to its study, and tremendous progress was made in identifying many of the transcription factors and regulatory DNA elements involved in the regulation of specific systems. However, very few attempts were made at going beyond these phenomenological and qualitative descriptions. Consequently, we are far from a quantitative and predictive understanding of transcriptional regulation. Through this program, I aim to develop a mechanistic understanding of transcriptional regulation, and for the first time model the entire process. We wish to go much beyond identifying and qualitatively describing the involved components, and arrive at a quantitative understanding of how transcriptional programs are encoded in the DNA sequences. To this end, my team and I will first work to mechanistically understand various building blocks of the transcriptional system, including: mechanisms of activation and repression; binding cooperativity; binding competition; transcription factors and chromatin interplay; architectural features of promoters that are important for its function; and the transcription functions “computed” by promoters. Since existing data are clearly insufficient for addressing such questions, I have opened an experimental lab and began to assemble a multidisciplinary team of scientists whose expertise span the experimental biology, computer science, physics, statistics, and mathematics disciplines, that will work synergistically to generate the appropriate data, analyze it, and use it to construct and experimentally validate models for the above transcriptional building blocks. We will then integrate all the insights gained into unified and quantitative models that should significantly enhance our understanding of the mechanistic workings of transcriptional regulation."
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