Đang chuẩn bị liên kết để tải về tài liệu:
Báo cáo y học: "Predicting domain-domain interactions using a parsimony approach"

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: Predicting domain-domain interactions using a parsimony approach. | Open Access Method Predicting domain-domain interactions using a parsimony approach Katia S Guimarães Ỷ Raja Jothi Elena Zotenko and Teresa M Przytycka Addresses National Center for Biotechnology Information National Library of Medicine National Institutes of Health Bethesda MD 20894 USA. Center of Informatics Federal University of Pernambuco Recife PE 50732 Brazil. Department of Computer Science University of Maryland College Park MD 20742 USA. Correspondence Teresa M Przytycka. Email przytyck@mail.nih.gov Published 9 November 2006 Genome Biology 2006 7 RI04 doi l0.ll86 gb-2006-7- ll-rl04 The electronic version of this article is the complete one and can be found online at http genomebiology.com 2006 7 ll Rl04 Received 26 June 2006 Revised 29 September 2006 Accepted 9 November 2006 2006 Guimarães et al licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License http creativecommons.org licenses by 2.0 which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Abstract We propose a novel approach to predict domain-domain interactions from a protein-protein interaction network. In our method we apply a parsimony-driven explanation of the network where the domain interactions are inferred using linear programming optimization and false positives in the protein network are handled by a probabilistic construction. This method outperforms previous approaches by a considerable margin. The results indicate that the parsimony principle provides a correct approach for detecting domain-domain contacts. Background Knowledge about protein interactions helps provide deeper insights into the functioning of cells. Protein interaction data are collected from various studies on individual biological systems and more recently through high-throughput experiments such as yeast two-hybrid and tandem affinity purification followed by mass spectrometry 1-8