• DocumentCode
    1150358
  • Title

    Multi-element probabilistic collocation for sensitivity analysis in cellular signalling networks

  • Author

    Foo, J. ; Sindi, S. ; Karniadakis, George E.

  • Author_Institution
    Div. of Appl. Math., Brown Univ., Providence, RI, USA
  • Volume
    3
  • Issue
    4
  • fYear
    2009
  • fDate
    7/1/2009 12:00:00 AM
  • Firstpage
    239
  • Lastpage
    254
  • Abstract
    The multi-element probabilistic collocation method (ME-PCM) as a tool for sensitivity analysis of differential equation models as applied to cellular signalling networks is formulated. This method utilises a simple, efficient sampling algorithm to quantify local sensitivities throughout the parameter space. The application of the ME-PCM to a previously published ordinary differential equation model of the apoptosis signalling network is presented. The authors verify agreement with the previously identified regions of sensitivity and then go on to analyse this region in greater detail with the ME-PCM. The authors demonstrate the generality of the ME-PCM by studying sensitivity of the system using a variety of biologically relevant markers in the system such as variation in one (or many) chemical species as a function of time, and total exposure of a single chemical species.
  • Keywords
    biology computing; cellular biophysics; differential equations; stochastic processes; apoptosis signalling network; cellular signalling networks; differential equation models; multielement probabilistic collocation method; sensitivity analysis;
  • fLanguage
    English
  • Journal_Title
    Systems Biology, IET
  • Publisher
    iet
  • ISSN
    1751-8849
  • Type

    jour

  • DOI
    10.1049/iet-syb.2008.0126
  • Filename
    5174553