• DocumentCode
    2857929
  • Title

    Stochastic Simulations of Cellular Biological Processes

  • Author

    Chushak, Yaroslav ; Foy, Brent ; Frazier, John

  • Author_Institution
    US Army Med. Res. & Materiel Command, Frederick
  • fYear
    2007
  • fDate
    18-21 June 2007
  • Firstpage
    425
  • Lastpage
    429
  • Abstract
    At the functional level, all biological processes in cells can be represented as a series of biochemical reactions that are stochastic in nature. We have developed a software package called biomolecular network simulator (BNS) that uses a stochastic approach to model and simulate complex biomolecular reaction networks. Two simulation algorithms-the exact Gillespie stochastic simulation algorithm and the approximate adaptive tau-leaping algorithm-are implemented for generating Monte Carlo trajectories that describe the evolution of a system of biochemical reactions. The software uses a combination of MATLAB and C-coded functions and is parallelized with the message passing interface (MPT) library to run on multiprocessor architectures.
  • Keywords
    Monte Carlo methods; biology computing; cellular biophysics; message passing; stochastic processes; Gillespie stochastic simulation algorithm; Monte Carlo trajectory; approximate adaptive tau-leaping algorithm; biomolecular network simulator; biomolecular reaction network; cellular biological process; message passing interface; software package; Biological processes; Biological system modeling; Cells (biology); Evolution (biology); MATLAB; Mathematical model; Monte Carlo methods; Software packages; Stochastic processes; Stochastic systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    DoD High Performance Computing Modernization Program Users Group Conference, 2007
  • Conference_Location
    Pittsburgh, PA
  • Print_ISBN
    978-0-7695-3088-5
  • Type

    conf

  • DOI
    10.1109/HPCMP-UGC.2007.70
  • Filename
    4438022