Genome Biol. 2004;5(6):R43. Epub 2004 May 28.

TXTGate: profiling gene groups with text-based information.

Glenisson P, Coessens B, Van Vooren S, Mathys J, Moreau Y, De Moor B.

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Departement Elektrotechniek (ESAT), Faculteit Toegepaste Wetenschappen, Katholieke Universiteit Leuven, Kasteelpark Arenberg 10, 3001 Heverlee (Leuven), Belgium.

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.

PMID:: 15186494; [PubMed - indexed for MEDLINE]
PMCID:: PMC463076

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