Automatic extension of Gene Ontology with flexible identification of candidate terms.
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.
Lee
Jin-Bok
JB
Computer Science Division and AITrc, KAIST 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, South Korea.
Kim
Jung-jae
JJ
Park
Jong C
JC
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
D011506:Proteins