• DocumentCode
    3230202
  • Title

    Incorporating ontology-driven similarity knowledge into functional genomics: an exploratory study

  • Author

    Azuaje, Francisco ; Bodenreider, Olivier

  • Author_Institution
    Ulster Univ., Jordanstown, UK
  • fYear
    2004
  • fDate
    19-21 May 2004
  • Firstpage
    317
  • Lastpage
    324
  • Abstract
    This research explores the feasibility of semantic similarity approaches to supporting predictive tasks in functional genomics. It aims to establish potential relationships between ontology-based similarity of gene products and important functional properties, such as gene expression correlation. Similarity measures based on the information content of the gene ontology (GO) were analyzed. Models have been implemented using data obtained from well-known studies in S. cerevisiae. Results suggest that there may exist significant relationships between gene expression correlation and semantic similarity. Analyses of protein complex data show that, in general, there is a significant correlation between the semantic similarity exhibited by a pair of genes and the probability of finding them in the same complex. These results can also be interpreted as an assessment of the quality and consistency of the information represented in the GO.
  • Keywords
    biology computing; genetics; information resources; knowledge representation; molecular biophysics; proteins; S. cerevisiae; functional genomics; gene expression correlation; gene ontology; information content; ontology-driven similarity knowledge; protein complex data; semantic similarity; Bioinformatics; Databases; Gene expression; Genomics; Large scale integration; Ontologies; Organisms; Predictive models; Proteins; Vocabulary;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Bioengineering, 2004. BIBE 2004. Proceedings. Fourth IEEE Symposium on
  • Print_ISBN
    0-7695-2173-8
  • Type

    conf

  • DOI
    10.1109/BIBE.2004.1317360
  • Filename
    1317360