IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v481y2017icp70-78.html
   My bibliography  Save this article

The stability of Boolean network with transmission sensitivity

Author

Listed:
  • Wang, Jiannan
  • Guo, Binghui
  • Wei, Wei
  • Mi, Zhilong
  • Yin, Ziqiao
  • Zheng, Zhiming

Abstract

Boolean network has been widely used in modeling biological systems and one of the key problems is its stability in response to small perturbations. Based on the hypothesis that the states of all nodes are homogenously updated, great progress has been made in previous works. In real biological networks, however, the updates of genes typically show much heterogeneity. To address such conditions, we introduce transmission sensitivity into Boolean network model. By the method of semi-annealed approximation, we illustrate that in a homogenous network, the critical condition of stability has no connection with its transmission sensitivity. As for heterogeneous networks, it reveals that correlations between network topology and transmission sensitivity can have profound effects on the its stability. This result shows a new mechanism that affects the stability of Boolean network, which could be used to control the dynamics in real biological systems.

Suggested Citation

  • Wang, Jiannan & Guo, Binghui & Wei, Wei & Mi, Zhilong & Yin, Ziqiao & Zheng, Zhiming, 2017. "The stability of Boolean network with transmission sensitivity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 481(C), pages 70-78.
  • Handle: RePEc:eee:phsmap:v:481:y:2017:i:c:p:70-78
    DOI: 10.1016/j.physa.2017.04.018
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437117303151
    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.2017.04.018?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. Wang, Jianjun & Liu, Wen & Fu, Shihua & Xia, Jianwei, 2022. "On robust set stability and set stabilization of probabilistic Boolean control networks," Applied Mathematics and Computation, Elsevier, vol. 422(C).
    2. Wouter Vermeer & Otto Koppius & Peter Vervest, 2018. "The Radiation-Transmission-Reception (RTR) model of propagation: Implications for the effectiveness of network interventions," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-21, December.

    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:481:y:2017:i:c:p:70-78. 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.