• DocumentCode
    3519850
  • Title

    Partial Order-Based Bayesian Network Learning Algorithm for Estimating Gene Networks

  • Author

    Numata, Kazuyuki ; Imoto, Seiya ; Miyano, Satoru

  • Author_Institution
    Human Genome Center, Univ. of Tokyo, Tokyo
  • fYear
    2008
  • fDate
    3-5 Nov. 2008
  • Firstpage
    357
  • Lastpage
    360
  • Abstract
    For learning Bayesian network structure from data, order-based algorithms such as K2 algorithm are widely used.In this paper, we consider a problem of constructing the order of nodes in such algorithms based on prior knowledge of gene networks. However, in many cases the prior knowledge is given as partial order of genes and we need to extend the order-based algorithm to partial order-based one. By extending our prior work we propose an efficient partial order-based algorithm for estimating gene networks based on Bayesian networks. The computational complexity of the proposed algorithm is shown.
  • Keywords
    belief networks; bioinformatics; genetics; learning (artificial intelligence); Bayesian network learning algorithm; K2 algorithm; gene networks estimation; partial order; Bayesian methods; Bioinformatics; Clustering algorithms; Computational Intelligence Society; Computational complexity; Gene expression; Genomics; Graphical models; Humans; Proteins; Bayesian network structure learning; gene regulatory networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedicine, 2008. BIBM '08. IEEE International Conference on
  • Conference_Location
    Philadelphia, PA
  • Print_ISBN
    978-0-7695-3452-7
  • Type

    conf

  • DOI
    10.1109/BIBM.2008.85
  • Filename
    4684919