• DocumentCode
    2414504
  • Title

    A new method for measuring the semantic similarity on gene ontology

  • Author

    Shen, Ying ; Zhang, Shaohong ; Wong, Hau-San

  • Author_Institution
    Dept. of Comput. Sci., City Univ. of Hong Kong, Hong Kong, China
  • fYear
    2010
  • fDate
    18-21 Dec. 2010
  • Firstpage
    533
  • Lastpage
    538
  • Abstract
    Semantic similarity defined on Gene Ontology (GO) aims to provide the functional relationship between different biological processes, molecular functions, or cellular components. In this paper, a novel method, namely the Shortest Path (SP) algorithm, for measuring the semantic similarity on GO is proposed based on both the GO structure information and the term´s property. The proposed algorithm searches for the shortest path that connects two terms and uses the sum of weights on the shortest path to compute the semantic similarity for GO terms. A method for evaluating the nonlinear correlation between two variables is also introduced for validation. Extensive experiments conducted on two public gene expression datasets demonstrate the overall superiority of SP method over the other state-of-the-art methods evaluated.
  • Keywords
    bioinformatics; cellular biophysics; genetics; molecular biophysics; ontologies (artificial intelligence); biological processes; cellular components; gene ontology; molecular functions; public gene expression datasets; semantic similarity; shortest path algorithm; Bioinformatics; Correlation; Gene expression; Integrated circuits; Joining processes; Ontologies; Semantics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedicine (BIBM), 2010 IEEE International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-8306-8
  • Electronic_ISBN
    978-1-4244-8307-5
  • Type

    conf

  • DOI
    10.1109/BIBM.2010.5706623
  • Filename
    5706623