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This article is part of the supplement: A critical assessment of text mining methods in molecular biology

Open Access Report

Text Detective: a rule-based system for gene annotation in biomedical texts

Javier Tamames

Author affiliations

Alma Bioinformatics S.L., Ronda de Poniente 4, 28750 Tres Cantos (Madrid), Spain

Citation and License

BMC Bioinformatics 2005, 6(Suppl 1):S10  doi:10.1186/1471-2105-6-S1-S10

Published: 24 May 2005

Abstract

Background

The identification of mentions of gene or gene products in biomedical texts is a critical step in the development of text mining applications in biosciences. The complexity and ambiguity of gene nomenclature makes this a very difficult task.

Methods

Here we present a novel approach based on a combination of carefully designed rules and several lexicons of biological concepts, implemented in the Text Detective system. Text Detective is able to normalize the results of gene mentions found by offering the appropriate database reference.

Results

In BioCreAtIvE evaluation, Text Detective achieved results of 84% precision, 71% recall for task 1A, and 79% precision, 71% recall for mouse genes in task 1B.