• DocumentCode
    1672071
  • Title

    Development of a particle simulator on cancer cell signaling network with PC cluster system

  • Author

    Ogawa, Makoto ; Nakakuki, Takashi ; Ishii, Chiharu ; Kobayashi, Mitsuo

  • Author_Institution
    Dept. of Mech. Syst. Eng., Kogakuin Univ., Tokyo, Japan
  • fYear
    2010
  • Firstpage
    2002
  • Lastpage
    2005
  • Abstract
    In various cancer cells, over-expression or mutation of epidermal growth factor (EGF) receptors is experimentally observed, and induces abnormal activation of intracellular signaling proteins, followed by continuous cell proliferation via dysfunctional gene regulatory networks. Since the activation process of EGF receptors on cell membrane is complicated and not fully understood, it is still a challenging work to develop the mathematical model from the viewpoint of cancer therapy such as drug discovery. In this paper, we develop a particle simulator on EGF-induced activation of EGF receptors on cell membrane. The engine of our simulator is based on the Hybrid Null-event Monte Carlo algorithm. The advantage is that our simulator is capable of evaluating ”lateral signaling” of EGF receptors, and directly comparing to the corresponding experimental data that shows a distribution of activated EGF receptors.
  • Keywords
    Monte Carlo methods; biology; cancer; differential equations; proteins; EGF receptors; PC cluster system; cancer cell signaling network; cancer therapy; cell membrane; dysfunctional gene regulatory networks; epidermal growth factor; hybrid null-event Monte Carlo algorithm; intracellular signaling proteins; particle simulator; Biological system modeling; Biomembranes; Cancer; Differential equations; Mathematical model; Modeling; Monte Carlo methods; EGF receptors; Monte Carlo simulation; lateral signaling; particle simulation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Automation and Systems (ICCAS), 2010 International Conference on
  • Conference_Location
    Gyeonggi-do
  • Print_ISBN
    978-1-4244-7453-0
  • Electronic_ISBN
    978-89-93215-02-1
  • Type

    conf

  • Filename
    5669749