• DocumentCode
    2564927
  • Title

    A memetic clustering algorithm for the functional partition of genes based on the gene ontology

  • Author

    Speer, Nora ; Spieth, Christian ; Zell, Andrea

  • Author_Institution
    Centre for Bioinformatics, Tubingen Univ., Germany
  • fYear
    2004
  • fDate
    7-8 Oct. 2004
  • Firstpage
    252
  • Lastpage
    259
  • Abstract
    With the invention of high throughput methods, researchers are capable of producing large amounts of biological data. During the analysis of such data the need of a functional grouping of genes arises. We propose a new clustering algorithm for the partition of genes or gene products according to their known biological function based on Gene Ontology terms. Ontologies offer a mechanism to capture knowledge in a shareable form that is also processable by computers. Our functional cluster algorithm promises to automatize, speed up and therefore improve biological data analysis.
  • Keywords
    biology computing; data analysis; genetics; ontologies (artificial intelligence); statistical analysis; biological data analysis; biological function; capture knowledge; functional partition; gene ontology; memetic clustering algorithm; Bioinformatics; Biology computing; Clustering algorithms; DNA; Data analysis; Databases; Genomics; Ontologies; Partitioning algorithms; Throughput;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence in Bioinformatics and Computational Biology, 2004. CIBCB '04. Proceedings of the 2004 IEEE Symposium on
  • Print_ISBN
    0-7803-8728-7
  • Type

    conf

  • DOI
    10.1109/CIBCB.2004.1393961
  • Filename
    1393961