IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v343y2004icp557-572.html
   My bibliography  Save this article

Population growth and control in stochastic models of cancer development

Author

Listed:
  • Ochab-Marcinek, Anna
  • Gudowska-Nowak, Ewa

Abstract

We study the joint effect of thermal bath fluctuations and an external noise tuning activity of cytotoxic cells on the triggered immune response in a growing cancerous tissue. The immune response is assumed to be primarily mediated by effector cells that develop a cytotoxic activity against the abnormal tissue. The kinetics of such a reaction is represented by an enzymatic-like Michaelis–Menten two step process. Effective free-energy surface for the process is further parameterised by the fluctuating energy barrier between the states of high and low concentration of cancerous cells. By analysing the far from equilibrium escape problem across the fluctuating potential barrier, we determine conditions of the most efficient decay kinetics of the cancer cell-population in the presence of dichotomously fluctuating concentration of cytotoxic cells.

Suggested Citation

  • Ochab-Marcinek, Anna & Gudowska-Nowak, Ewa, 2004. "Population growth and control in stochastic models of cancer development," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 343(C), pages 557-572.
  • Handle: RePEc:eee:phsmap:v:343:y:2004:i:c:p:557-572
    DOI: 10.1016/j.physa.2004.06.071
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437104008714
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2004.06.071?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mansour, Mahmoud B.A. & Abobakr, Asmaa H., 2022. "Stochastic differential equation models for tumor population growth," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:343:y:2004:i:c:p:557-572. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.