• DocumentCode
    3542535
  • Title

    Pathway analysis in the context of Bayesian networks - mathematical modeling of master and canalizing genes

  • Author

    Zhao, Chen ; Ivanov, Ivan ; Bittner, Michael L. ; Dougherty, Edward R.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Texas A&M Univ., College Station, TX, USA
  • fYear
    2011
  • fDate
    4-6 Dec. 2011
  • Firstpage
    64
  • Lastpage
    65
  • Abstract
    We utilize a tree-structured Bayesian network to characterize and detect master and canalizing genes via the coefficient of determination (CoD). Master genes possess strong regulation over groups of genes, whereas canalizing genes take over the regulation of large cohorts under certain cell conditions. While related, the two concepts are not the same and the analytic measures we employ reveal that difference. We also consider hypothesis testing for successful drug intervention in the framework of the Bayesian model.
  • Keywords
    belief networks; drugs; genetics; genomics; physiological models; signal processing; Bayesian networks; canalizing genes; coefficient of determination; drug intervention; hypothesis testing; master genes; pathway analysis; signal-processing model; Bayesian methods; Bioinformatics; Computational modeling; Drugs; Histograms; Irrigation; USA Councils;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Genomic Signal Processing and Statistics (GENSIPS), 2011 IEEE International Workshop on
  • Conference_Location
    San Antonio, TX
  • ISSN
    2150-3001
  • Print_ISBN
    978-1-4673-0491-7
  • Electronic_ISBN
    2150-3001
  • Type

    conf

  • DOI
    10.1109/GENSiPS.2011.6169444
  • Filename
    6169444