Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học Wertheim cung cấp cho các bạn kiến thức về ngành y đề tài: Explicit equilibrium modeling of transcription-factor binding and gene regulation. | Method Open Access Explicit equilibrium modeling of transcription-factor binding and gene regulation Joshua A Granek and Neil D Clarke Addresses Department of Biophysics and Biophysical Chemistry Johns Hopkins University School of Medicine North Wolfe Street Baltimore MD 21205 USA. National Evolutionary Synthesis Center Broad Street Durham NC 27705 USA. Genome Institute of Singapore Biopolis Street Singapore 138672 Republic of Singapore. Correspondence Neil D Clarke. E-mail nclarke@ Published 30 September 2005 Genome Biology 2005 6 R87 doi 186 gb-2005-6-10-r87 The electronic version of this article is the complete one and can be found online at http 2005 6 10 R87 Received 3 May 2005 Revised 17 June 2005 Accepted 30 August 2005 2005 Granek and Clarke licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License http licenses by which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Abstract We have developed a computational model that predicts the probability of transcription factor binding to any site in the genome. GOMER generalizable occupancy model of expression regulation calculates binding probabilities on the basis of position weight matrices and incorporates the effects of cooperativity and competition by explicit calculation of coupled binding equilibria. GOMER can be used to test hypotheses regarding gene regulation that build upon this physically principled prediction of protein-DNA binding. Background Transcription is regulated by the binding of proteins to specific DNA sequences. Until recently binding and regulation could only be studied at the level of individual genes but they can now be studied as a complex system due to the availability of genome-wide data on expression and transcription factor binding. Computational models are needed however to evaluate .
