tailieunhanh - Báo cáo y học: "TXTGate: profiling gene groups with text-based information"

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: TXTGate: profiling gene groups with text-based information. | Software Open Access TXTGate profiling gene groups with text-based information Patrick Glenisson Bert Coessens Steven Van Vooren Janick Mathys Yves Moreau and Bart De Moor Addresses Departement Elektrotechniek ESAT Faculteit Toegepaste Wetenschappen Katholieke Universiteit Leuven Kasteelpark Arenberg 10 3001 Heverlee Leuven Belgium. Current address Center for Biological Sequence Analysis BioCentrum Danish Technical University Kemitorvet DK-2800 Lyngby Denmark. Correspondence Bert Coessens. E-mail Published 28 May 2004 Genome Biology 2004 5 R43 The electronic version of this article is the complete one and can be found online at http 2004 5 6 R43 Received 24 November 2003 Revised 3 February 2004 Accepted 27 April 2004 2004 Glenisson et al. licensee BioMed Central Ltd. This is an Open Access article verbatim copying and redistribution of this article are permitted in all media for any purpose provided this notice is preserved along with the article s original URL. Abstract We implemented a framework called TXTGate that combines literature indices of selected public biological resources in a flexible text-mining system designed towards the analysis of groups of genes. By means of tailored vocabularies term- as well as gene-centric views are offered on selected textual fields and MEDLINE abstracts used in LocusLink and the Saccharomyces Genome Database. Subclustering and links to external resources allow for in-depth analysis of the resulting term profiles. Rationale Recent advances in high-throughput methods such as microarrays enable systematic testing of the functions of multiple genes their interrelatedness and the controlled circumstances in which ensuing observations hold. As a result scientific discoveries and hypotheses are stacking up all primarily reported in the form of free text. However as large amounts of raw textual data are hard to extract information from various specialized databases have been .

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