Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học Minireview cung cấp cho các bạn kiến thức về ngành y đề tài: Statistical assessment of the global regulatory role of histone acetylation in Saccharomyces cerevisiae. | Research Open Access Statistical assessment of the global regulatory role of histone acetylation in Saccharomyces cerevisiae Guo-Cheng YuanH Ping MaH Wenxuan Zhong and Jun S Liu Addresses Department of Statistics Harvard University Cambridge MA 02138 USA. tBauer Center for Genomics Research Harvard University Cambridge MA 02138 USA. Department of Statistics University of Illinois Champaign IL 61820 USA. Institute for Genomic Biology University of Illinois Champaign IL 61820 USA. H These authors contributed equally to this work. Correspondence Jun S Liu. Email jliu@ Published 2 August 2006 Genome Biology 2006 7 R70 doi l86 gb-2006-7-8-r70 The electronic version of this article is the complete one and can be found online at http 2006 7 8 R70 Received 5 April 2006 Revised 5 June 2006 Accepted 2 August 2006 2006 Yuan et al. 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 Background Histone acetylation plays important but incompletely understood roles in gene regulation. A comprehensive understanding of the regulatory role of histone acetylation is difficult because many different histone acetylation patterns exist and their effects are confounded by other factors such as the transcription factor binding sequence motif information and nucleosome occupancy. Results We analyzed recent genomewide histone acetylation data using a few complementary statistical models and tested the validity of a cumulative model in approximating the global regulatory effect of histone acetylation. Confounding effects due to transcription factor binding sequence information were estimated by using two independent motif-based algorithms followed by a variable selection method. We found that the sequence .
