title: Finding genomic ontology terms in text using evidence content.
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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Departamento de Informática, Faculdade de Ciências, Universidade de Lisboa, Portugal. fcouto@di.fc.ul.pt
authors.forename: Francisco M
authors.initials: FM
authors.lastname: Couto
authors.forename: Mário J
authors.initials: MJ
authors.lastname: Silva
authors.forename: Pedro M
authors.initials: PM
authors.lastname: Coutinho
mesh_terms: D019295:Computational Biology / Q000379:methods*; D023281:Genomics / Q000145:classification*; D010363:Pattern Recognition, Automated / Q000379:methods*; D010506:Periodicals as Topic; D009626:Terminology as Topic; D013782:Textbooks as Topic; D014956:Writing