TAILIEUCHUNG - Báo cáo y học: "Consolidating the set of known human protein-protein interactions in preparation for large-scale mapping of the human interactome"

Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học Wertheim cung cấp cho các bạn kiến thức về ngành y đề tài: Consolidating the set of known human protein-protein interactions in preparation for large-scale mapping of the human interactome. | Research Open Access Consolidating the set of known human protein-protein interactions in preparation for large-scale mapping of the human interactome Arun K Ramani Razvan C Bunescu Raymond J Mooneye and Edward M Marcotte Addresses Center for Systems and Synthetic Biology and Institute for Cellular and Molecular Biology University of Texas Austin TX 78712 USA. Department of Computer Sciences University of Texas Austin TX 78712 USA. Department of Chemistry and Biochemistry University of Texas Austin TX 78712 USA. Correspondence RaymondJ Mooney. E-mail mooney@. Edward M Marcotte. E-mail marcotte@. Published 15 April 2005 Genome Biology 2005 6 R40 doi 186 gb-2005-6-5-R40 The electronic version of this article is the complete one and can be found online at http 2005 6 5 r40 Received 20 December 2004 Revised 9 February 2005 Accepted 11 March 2005 2005 Marcotte 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 Extensive protein interaction maps are being constructed for yeast worm and fly to ask how the proteins organize into pathways and systems but no such genome-wide interaction map yet exists for the set of human proteins. To prepare for studies in humans we wished to establish tests for the accuracy of future interaction assays and to consolidate the known interactions among human proteins. Results We established two tests of the accuracy of human protein interaction datasets and measured the relative accuracy of the available data. We then developed and applied natural language processing and literature-mining algorithms to recover from Medline abstracts 6 580 interactions among 3 737 human proteins. A three-part algorithm was used first human .

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