• DocumentCode
    1797931
  • Title

    A hybrid measure for the semantic similarity of gene ontology terms

  • Author

    Shu-Bo Zhang ; Jian-Huang Lai

  • Author_Institution
    Dept. of Comput. Sci., Guangzhou Maritime Inst., Guangzhou, China
  • fYear
    2014
  • fDate
    15-17 Nov. 2014
  • Firstpage
    911
  • Lastpage
    916
  • Abstract
    Measuring the semantic similarity between pairs of terms in Gene Ontology (GO) can help to compare genes that can not be compared by other computational methods. In this study, we proposed a hybrid method to calculate the semantic similarity between two GO terms by taking into account multiple common ancestors of they have in common, and aggregating the semantic information and depth information of the non-redundant common ancestors. Our method searches for non-redundant common ancestors in an effective way. Validation experiments were conducted on both expression dataset and pathway dataset, and the experimental results suggest the superiority of our method against some existing methods.
  • Keywords
    biology computing; genetics; ontologies (artificial intelligence); GO terms; depth information; gene ontology; hybrid measure; nonredundant common ancestors; semantic information; semantic similarity; Biomedical measurement; Databases; Degradation; Gene expression; Ontologies; Semantics; GO terms; Gene Ontology (GO); biological pathways; gene expression profile; semantic similarity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems and Informatics (ICSAI), 2014 2nd International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4799-5457-5
  • Type

    conf

  • DOI
    10.1109/ICSAI.2014.7009415
  • Filename
    7009415