TXTGate: profiling gene groups with text-based information

200467 citationsJournal Articlegold Open Access

Authors

Patrick Glenisson · KU Leuven

Bert Coessens · KU Leuven

Steven Van Vooren · KU Leuven

Janick Mathys · KU Leuven

Yves Moreau · Technical University of Denmark

Bart De Moor · KU Leuven

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.

Topics & Keywords

Biomedical Text Mining and Ontologies Genomics and Phylogenetic Studies Bioinformatics and Genomic Networks

UN Sustainable Development Goals

Quality Education

Publication Details

Published in: Genome biology

Volume 5, Issue 6, pp. R43-R43

DOI: 10.1186/gb-2004-5-6-r43

Field-Weighted Citation Impact: 3.36