tailieunhanh - Báo cáo y học: "Discovery of biological networks from diverse functional genomic data"

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: Discovery of biological networks from diverse functional genomic data. | Method Open Access Discovery of biological networks from diverse functional genomic data Chad L Myers Drew Robson Adam Wible Matthew A Hibbs Camelia Chiriac Chandra L Theesfeld Kara Dolinski and Olga G Troyanskaya Addresses Department of Computer Science Princeton University 35 Olden Street Princeton NJ 08544 USA. Lewis-Sigler Institute for Integrative Genomics Carl Icahn Laboratory Princeton University Princeton NJ 08544 USA. Department of Mathematics Princeton University Washington Road Princeton NJ 08540 USA. Department of Genetics School of Medicine Mailstop-Si20 Stanford University Stanford CA 94305-5120 USA. Correspondence OlgaGTroyanskaya. E-mail ogt@ Published 19 December 2005 Genome Biology 2005 6 R1 14 doi gb-2005-6-13-r114 The electronic version of this article is the complete one and can be found online at http 2005 6 13 R1 14 Received 1 July 2005 Revised 3 1 August 2005 Accepted 21 November 2005 2005 Myers 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 We have developed a general probabilistic system for query-based discovery of pathway-specific networks through integration of diverse genome-wide data. This framework was validated by accurately recovering known networks for 31 biological processes in Saccharomyces cerevisiae and experimentally verifying predictions for the process of chromosomal segregation. Our system bioPIXIE a public comprehensive system for integration analysis and visualization of biological network predictions for S. cerevisiae is freely accessible over the worldwide web. Background Understanding biological networks on a whole-genome scale is a key challenge in modern systems biology. Broad availability of diverse functional .