IDEAS home Printed from https://ideas.repec.org/a/spr/eurphb/v89y2016i6d10.1140_epjb_e2016-70172-9.html
   My bibliography  Save this article

Design of artificial genetic regulatory networks with multiple delayed adaptive responses

Author

Listed:
  • Pablo Kaluza

    (National Scientific and Technical Research Council and Faculty of Exact and Natural Sciences, National University of Cuyo
    Abteilung Physikalische Chemie, Fritz-Haber-Institut der Max-Planck-Gesellschaft)

  • Masayo Inoue

    (Molecular Profiling Research Center for Drug Discovery, National Institute of Advanced Industrial Science and Technology
    Cybermedia Center, Osaka University)

Abstract

Genetic regulatory networks with adaptive responses are widely studied in biology. Usually, models consisting only of a few nodes have been considered. They present one input receptor for activation and one output node where the adaptive response is computed. In this work, we design genetic regulatory networks with many receptors and many output nodes able to produce delayed adaptive responses. This design is performed by using an evolutionary algorithm of mutations and selections that minimizes an error function defined by the adaptive response in signal shapes. We present several examples of network constructions with a predefined required set of adaptive delayed responses. We show that an output node can have different kinds of responses as a function of the activated receptor. Additionally, complex network structures are presented since processing nodes can be involved in several input-output pathways.

Suggested Citation

  • Pablo Kaluza & Masayo Inoue, 2016. "Design of artificial genetic regulatory networks with multiple delayed adaptive responses," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 89(6), pages 1-11, June.
    • Handle: RePEc:spr:eurphb:v:89:y:2016:i:6:d:10.1140_epjb_e2016-70172-9
    DOI: 10.1140/epjb/e2016-70172-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1140/epjb/e2016-70172-9
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1140/epjb/e2016-70172-9?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.

    More about this item

    Keywords

    Statistical and Nonlinear Physics;

    Statistics

    Access and download statistics

    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:spr:eurphb:v:89:y:2016:i:6:d:10.1140_epjb_e2016-70172-9. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.