This article is part of the supplement: A critical assessment of text mining methods in molecular biology
Finding genomic ontology terms in text using evidence content
1 Departamento de Informática, Faculdade de Ciências da Universidade de Lisboa, Portugal
2 Architecture et Fonction des Macromolécules Biologiques, CNRS, Marseille, France
BMC Bioinformatics 2005, 6(Suppl 1):S21 doi:10.1186/1471-2105-6-S1-S21Published: 24 May 2005
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.
This document introduces a novel unsupervised method for recognizing biological properties in unstructured text, involving the evidence content of their names.
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.
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.