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Báo cáo y học: "MONKEY: identifying conserved transcription-factor binding sites in multiple alignments using a binding site-specific evolutionary model"

Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học quốc tế cung cấp cho các bạn kiến thức về ngành y đề tài: MONKEY: identifying conserved transcription-factor binding sites in multiple alignments using a binding site-specific evolutionary model. | Open Access Method MONKEY identifying conserved transcription-factor binding sites in multiple alignments using a binding site-specific evolutionary model Alan M Moses Derek Y Chiang Daniel A Pollard Venky N Iyer and Michael B Eisen Addresses Graduate Group in Biophysics University of California Berkeley CA 94720 USA. Center for Integrative Genomics University of California Berkeley CA 94720. Department of Molecular and Cell Biology University of California Berkeley CA 94720 USA. Department of Genome Sciences Genomics Division Ernest Orlando Lawrence Berkeley National Lab 1 Cyclotron Road CA 942770 USA. Correspondence Michael B Eisen. E-mail mbeisen@lbl.gov Published 30 November 2004 Genome Biology 2004 5 R98 The electronic version of this article is the complete one and can be found online at http genomebiology.com 2004A5 12 R98 Received 28 August 2004 Revised 21 October 2004 Accepted 28 October 2004 2004 Moses et al licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License http creativecommons.org licenses by 2.0 which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Abstract We introduce a method MONKEY to identify conserved transcription-factor binding sites in multispecies alignments. MONKEY employs probabilistic models of factor specificity and bindingsite evolution on which basis we compute the likelihood that putative sites are conserved and assign statistical significance to each hit. Using genomes from the genus Saccharomyces we illustrate how the significance of real sites increases with evolutionary distance and explore the relationship between conservation and function. Background Different types of genomic features have characteristic patterns of evolution that when sequences from closely related organisms are available can be exploited to annotate genomes 1 . Methods for comparative sequence analysis that exploit