Literature DB >> 16428805

Automatic extension of Gene Ontology with flexible identification of candidate terms.

Jin-Bok Lee1, Jung-jae Kim, Jong C Park.   

Abstract

MOTIVATION: 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. AVAILABILITY: http://autogo.biopathway.org SUPPLEMENTARY INFORMATION: Supplementary materials are available at Bioinformatics online.

Mesh:

Substances:

Year:  2006        PMID: 16428805     DOI: 10.1093/bioinformatics/btl010

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  4 in total

1.  Semi-automated ontology generation within OBO-Edit.

Authors:  Thomas Wächter; Michael Schroeder
Journal:  Bioinformatics       Date:  2010-06-15       Impact factor: 6.937

2.  Predicting the extension of biomedical ontologies.

Authors:  Catia Pesquita; Francisco M Couto
Journal:  PLoS Comput Biol       Date:  2012-09-13       Impact factor: 4.475

3.  Combining lexical and context features for automatic ontology extension.

Authors:  Sara Althubaiti; Şenay Kafkas; Marwa Abdelhakim; Robert Hoehndorf
Journal:  J Biomed Semantics       Date:  2020-01-13

4.  Monitoring the evolutionary aspect of the Gene Ontology to enhance predictability and usability.

Authors:  Jong C Park; Tak-eun Kim; Jinah Park
Journal:  BMC Bioinformatics       Date:  2008-04-11       Impact factor: 3.169

  4 in total

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