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TXTGate: profiling gene groups with text-based information.

Patrick Glenisson·Bert Coessens·Steven Van Vooren·Janick Mathys·Yves Moreau·Bart De Moor
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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.

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AnimalsCluster AnalysisDatabases, GeneticDisease Models, AnimalGene Expression ProfilingGene Expression Regulation, FungalGene Expression Regulation, NeoplasticGenes, FungalGenes, NeoplasmGenome, FungalGenome, HumanHumansInformation Storage and RetrievalMEDLINEMiceSaccharomycesSalivary Gland NeoplasmsVocabularyComparative StudyJournal ArticleResearch Support, Non-U.S. Gov't

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Patrick Glenisson, Bert Coessens, Steven Van Vooren, Janick Mathys, Yves Moreau, Bart De Moor. 2004-05-28. TXTGate: profiling gene groups with text-based information.. https://doi.org/10.1186/gb-2004-5-6-r43

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