PLOS Comp Bio 2010 Paper
Thermodynamics-based models of transcriptional regulation by enhancers: the roles of synergistic activation, cooperative binding and short-range repression
Xin He1, Md. Abul Hassan Samee2, Charles Blatti2, and Saurabh Sinha2,*
1Department of Biochemistry and Biophysics, University of California at San Francisco
2Department of Computer Science, University of Illinois at Urbana-Champaign
*To whom correspondence should be addressed, sinhas@illinois.edu
Work supported by NSF CAREER grant DBI-0746303 and NIH grant 1R01GM085233-01.
We have developed a thermodynamics-based model to predict gene expression driven by any DNA sequence, as a function of transcription factor concentrations and their DNA-binding specificities. It uses statistical thermodynamics theory to model not only protein-DNA interaction, but also the effect of DNA-bound activators and repressors on gene expression. In addition, the model incorporates various mechanistic features such as synergistic effect of multiple activators, short range repression, and cooperativity in transcription factor-DNA binding, allowing us to systematically evaluate the significance of these features in the context of available expression data. Our implementation of the model, called GEMSTAT, can be downloaded for free from the following link. To use the program, extract the .tar.gz file, and go through the README.txt file for detailed instructions on compiling and executing the program.