Automatically generating stochastic models of transcriptional regulation (PDF)

Robin Dowell, Assistant Professor, University of Colorado - MCD Biology

4/23/2012, 2:00PM, GHC-6121


Transcriptional regulation is the complex system of interactions used to produce precise gene expression at specific times and locations. Encapsulating our understanding of these interactions in computational models allows the exploration and prediction of the cellular response to changing environments, which can provide invaluable support and guidance to experimental research. We present a method for generating rules for a stochastic simulation of the transcription process for any DNA sequence in a well-characterized genome.  Our method incorporates transcription factor binding, nucleosome positioning, the effects of transcriptional interference, and the chromatin remodeling events of the transcriptional machinery into a single unified model of the transcription process.


Robin Dowell is an Assistant Professor in the Molecular, Cellular and Developmental Biology and Computer Science Departments and the Biofrontiers Institute at the University of Colorado in Boulder.  Her laboratory uses a combination of  computational, experimental, algorithmic, and systems biology approaches to the study of transcriptional regulation, with particular focus on how variation in the noncoding portion of the genome impacts the evolution of regulation.  Previously Dr. Dowell worked as a postdoc at the MIT Computer Science and Artificial Intelligence Laboratory and received her doctorate (in Biomedical Engineering) and masters (in Computer Science) from the University of Washington in St. Louis.


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nsfSupported by an Expeditions in Computing award from the National Science Foundation