title: Automatic extension of Gene Ontology with flexible identification of candidate terms.
abstract: BACKGROUND
  Gene Ontology (GO) has been manually developed to provide a controlled vocabulary for gene product attributes. It continues to evolve with new concepts that are compiled mostly from existing concepts in a compositional way. If we consider the relatively slow growth rate of GO in the face of the fast accumulation of the biological data, it is much desirable to provide an automatic means for predicting new concepts from the existing ones.
  
  
  RESULTS
  We present a novel method that predicts more detailed concepts by utilizing syntactic relations among the existing concepts. We propose a validation measure for the automatically predicted concepts by matching the concepts to biomedical articles. We also suggest how to find a suitable direction for the extension of a constantly growing ontology such as GO.
  
  
  BACKGROUND
  http://autogo.biopathway.org
  
  
  BACKGROUND
  Supplementary materials are available at Bioinformatics online.
authors.affiliation: Computer Science Division and AITrc, KAIST 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, South Korea.
authors.forename: Jin-Bok
authors.initials: JB
authors.lastname: Lee
authors.forename: Jung-jae
authors.initials: JJ
authors.lastname: Kim
authors.forename: Jong C
authors.initials: JC
authors.lastname: Park
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003628:Database Management Systems; D030562:Databases, Protein; D004282:Documentation / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D009323:Natural Language Processing; D010363:Pattern Recognition, Automated / Q000379:methods*; D011506:Proteins / Q000145:classification*; D018875:Vocabulary, Controlled
chemical_list: D011506:Proteins