TXTGate: profiling gene groups with text-based inf...[Genome Biol. 2004]

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

TXTGate: profiling gene groups with text-based information.

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

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

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

Clustering gene expression data using adaptive double self-organizing map. [Physiol Genomics. 2003]
Mining microarray expression data by literature profiling. [Genome Biol. 2002]
Using text analysis to identify functionally coherent gene groups. [Genome Res. 2002]
CoPub Mapper: mining MEDLINE based on search term co-publication. [BMC Bioinformatics. 2005]
Text mining biomedical literature for discovering gene-to-gene relationships: a comparative study of algorithms. [IEEE/ACM Trans Comput Biol Bioinform. 2005]
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TXTGate: profiling gene groups with text-based information.

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