tailieunhanh - Báo cáo y học: "InSite: a computational method for identifying protein-protein interaction binding sites on a proteome-wide scale"

Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học Critical Care giúp cho các bạn có thêm kiến thức về ngành y học đề tài:InSite: a computational method for identifying protein-protein interaction binding sites on a proteome-wide scale. | Open Access Method InSite a computational method for identifying protein-protein interaction binding sites on a proteome-wide scale Haidong Wang Eran Segal Asa Ben-Hur Qian-Ru Li Marc Vidal and Daphne Koller Addresses Computer Science Department Stanford University Serra Mall Stanford CA 94305 USA. Department of Computer Science and Applied Mathematics Weizmann Institute of Science Rehovot 76100 Israel. Computer Science Department Colorado State University South Howes Street Fort Collins CO 80523 USA. Center for Cancer Systems Biology CCSB and Department of Cancer Biology Dana-Farber Cancer Institute and Department of Genetics Harvard Medical School Binney Street Boston MA 02115 USA. Correspondence Daphne Koller. Email koller@ Published 14 September 2007 Genome Biology 2007 8 RI92 doi gb-2007-8-9-rI 92 The electronic version of this article is the complete one and can be found online at http 2007 8 9 RI92 Received 7 March 2007 Revised 25 July 2007 Accepted I4 September 2007 2007 Wang 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 propose InSite a computational method that integrates high-throughput protein and sequence data to infer the specific binding regions of interacting protein pairs. We compared our predictions with binding sites in Protein Data Bank and found significantly more binding events occur at sites we predicted. Several regions containing disease-causing mutations or cancer polymorphisms in human are predicted to be binding for protein pairs related to the disease which suggests novel mechanistic hypotheses for several diseases. Background Much recent work focuses on generating proteome-wide protein-protein interaction maps for both model .