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Bioinformatics Advance Access originally published online on April 1, 2004
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Bioinformatics 20(13) © Oxford University Press 2004; all rights reserved.

Gene annotation from scientific literature using mappings between keyword systems

Antonio J. Pérez 1, Carolina Perez-Iratxeta 2,3,{dagger}, Peer Bork 2,3, Guillermo Thode 1 and Miguel A. Andrade 2,3,*,{dagger}

1 University of Málaga, Facultad de Ciencias, Departmento de Genetica, Group of Bioinformatics, Campus Universitario de Teatinos, 29071 Málaga, Spain, 2 European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany and 3 Max Delbrück Center for Molecular Medicine, Department of Bioinformatics, PO Box 740238, 13092 Berlin-Buch, Germany

Received on October 17, 2003; revised on January 7, 2004; accepted on January 19, 2004
Advance Access Publication April 1, 2004

Motivation: The description of genes in databases by keywords helps the non-specialist to quickly grasp the properties of a gene and increases the efficiency of computational tools that are applied to gene data (e.g. searching a gene database for sequences related to a particular biological process). However, the association of keywords to genes or protein sequences is a difficult process that ultimately implies examination of the literature related to a gene.

Results: To support this task, we present a procedure to derive keywords from the set of scientific abstracts related to a gene. Our system is based on the automated extraction of mappings between related terms from different databases using a model of fuzzy associations that can be applied with all generality to any pair of linked databases. We tested the system by annotating genes of the SWISS-PROT database with keywords derived from the abstracts linked to their entries (stored in the MEDLINE database of scientific references). The performance of the annotation procedure was much better for SWISS-PROT keywords (recall of 47%, precision of 68%) than for Gene Ontology terms (recall of 8%, precision of 67%).

Availability: The algorithm can be publicly accessed and used for the annotation of sequences through a web server at http://www.bork.embl.de/kat

Contact: mandrade{at}ohri.ca

* To whom correspondence should be addressed.

{dagger} Present address: Ottawa Health Research Centre, 501 Smyth Road, Ottawa, Ontario K1H 8L6, Canada.


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