• DocumentCode
    2174244
  • Title

    Hybrid identification methods for the reconstruction of Genetic Regulatory Networks

  • Author

    Ferrari-Trecate, Giancarlo

  • Author_Institution
    Dept. of Comput. Eng. & Syst. Sci., Univ. of Pavia, Pavia, Italy
  • fYear
    2007
  • fDate
    2-5 July 2007
  • Firstpage
    4845
  • Lastpage
    4852
  • Abstract
    This tutorial paper considers the problem of reconstructing Genetic Regulatory Networks (GRNs) from gene expression measurements. Among various modeling frameworks that have been proposed for these biological systems, we focus on PieceWise Affine (PWA) models because of their ability to capture both the switching behavior of genes and the continuous dynamics of molecule concentrations. PWA models of GRNs have a special structure that must be preserved by the identification process. In the paper, we discuss the new challenges that this constraint raises in the field of hybrid identification. As an example, we summarize recently proposed methods for detecting switches in gene expression profiles and for reconstructing multiple PWA models consistent with the data. We also present the results obtained by applying these algorithms to synthetic data produced by PWA models of the GRN governing the carbon starvation response in E. coli.
  • Keywords
    biology; genetics; E. coli; GRN; PWA models; biological systems; carbon starvation; continuous dynamics; gene expression measurements; gene expression profiles; genetic regulatory network reconstruction; hybrid identification field; hybrid identification methods; identification process; molecule concentrations; piecewise affine models; switching behavior; Biological system modeling; Computational modeling; Data models; Gene expression; Indexes; Proteins; Switches;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (ECC), 2007 European
  • Conference_Location
    Kos
  • Print_ISBN
    978-3-9524173-8-6
  • Type

    conf

  • Filename
    7069043