• DocumentCode
    2915428
  • Title

    Toward a gene regulatory network model for evolving chemotaxis behavior

  • Author

    Samways, Neale ; Jin, Yaochu ; Yao, Xin ; Sendhoff, Bernhard

  • Author_Institution
    Sch. of Comput. Sci., Birmingham Univ., Birmingham
  • fYear
    2008
  • fDate
    1-6 June 2008
  • Firstpage
    2569
  • Lastpage
    2576
  • Abstract
    Inspired from bacteria, a gene regulatory network model for signal transduction is presented in this paper. After describing experiments on stabilizing the population size for sustained open-ended evolution, we examine the ability of the model to evolve gradient-following behavior resembling bacterial chemotaxis. Under the conditions defined in this paper, an overwhelming chemotaxis behavior does not seem to emerge. Further experimentation suggests that chemotaxis is selectively favored, however, it is shown that the gradient information, which is critical for evolving chemotaxis, is heavily degraded under the current regime. It is hypothesized that lack of consistent gradient information results in the selection of non chemotaxis behavior. Future work on revising the model as well as the environmental setups is discussed.
  • Keywords
    biology; evolutionary computation; bacterial chemotaxis; evolving chemotaxis behavior; gene regulatory network model; gradient information; open-ended evolution; signal transduction; Biological information theory; Biological system modeling; Biology computing; Chemistry; Environmental factors; Evolution (biology); Genetics; Microorganisms; Organisms; Proteins;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-1822-0
  • Electronic_ISBN
    978-1-4244-1823-7
  • Type

    conf

  • DOI
    10.1109/CEC.2008.4631143
  • Filename
    4631143