TAILIEUCHUNG - Báo cáo sinh học: "Comprehensive curation and analysis of global interaction networks in Saccharomyces cerevisiae"

Tuyển tập các báo cáo nghiên cứu về sinh học được đăng trên tạp chí sinh học Journal of Biology đề tài: Comprehensive curation and analysis of global interaction networks in Saccharomyces cerevisiae. | J. Biol. Journal of Biology BioMed Central Research article Open Access Comprehensive curation and analysis of global interaction networks in Saccharomyces cerevisiae Teresa Reguly Ashton Breitkreutz Lorrie Boucher Bobby-Joe Breitkreutz Gary C Hon Chad L Myers Ainslie Parsons Helena Friesen Rose Oughtred Amy Tong Chris Stark Yuen Ho David Botstein Brenda Andrews Charles Boone Olga G Troyanskya Trey Ideker Kara Dolinski Nizar N Batada and Mike Tyers Addresses Samuel Lunenfeld Research Institute Mount Sinai Hospital Toronto ON M5G 1X5 Canada . tDepartment of Medical Genetics and Microbiology University of Toronto Toronto ON M5S 1A8 Canada. Department of Bioengineering University of California San Diego 9500 Gilman Drive La Jolla CA 92093-0412 USA . Lewis-Sigler Institute for Integrative Genomics Princeton University Washington Road Princeton NJ 08544 USA. Department of Computer Science Princeton University NJ 08544 USA. Banting and Best Department of Medical Research University of Toronto Toronto ON M5G 1L6 Canada. These authors contributed equally to this work Correspondence Mike Tyers. Email tyers@ Published 8 June 2006 Received 18 October 2005 Journal of Biology 2006 5 11 The electronic version of this article is the complete one and can be found online at http content 5 4 11 Revised 17 March 2006 Accepted 30 March 2006 2006 Reguly and Breitkreutz 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 The study of complex biological networks and prediction of gene function has been enabled by high-throughput HTP methods for detection of genetic and protein interactions. Sparse coverage in HTP datasets may however distort network properties and confound predictions. Although a vast .

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