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

Open Access Report

Finding genomic ontology terms in text using evidence content

Francisco M Couto1*, Mário J Silva1 and Pedro M Coutinho2

Author Affiliations

1 Departamento de Informática, Faculdade de Ciências da Universidade de Lisboa, Portugal

2 Architecture et Fonction des Macromolécules Biologiques, CNRS, Marseille, France

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BMC Bioinformatics 2005, 6(Suppl 1):S21  doi:10.1186/1471-2105-6-S1-S21

Published: 24 May 2005

Abstract

Background

The development of text mining systems that annotate biological entities with their properties using scientific literature is an important recent research topic. These systems need first to recognize the biological entities and properties in the text, and then decide which pairs represent valid annotations.

Methods

This document introduces a novel unsupervised method for recognizing biological properties in unstructured text, involving the evidence content of their names.

Results

This document shows the results obtained by the application of our method to BioCreative tasks 2.1 and 2.2, where it identified Gene Ontology annotations and their evidence in a set of articles.

Conclusion

From the performance obtained in BioCreative, we concluded that an automatic annotation system can effectively use our method to identify biological properties in unstructured text.