Gene regulation in a particle metabolome

  • Authors:

  • Simon Hickinbotham;Edward Clark;Susan Stepney;Tim Clarke;Peter Young

  • Affiliations:

  • York Centre for Complex Systems Analysis, University of York, Heslington, York, UK;York Centre for Complex Systems Analysis, University of York, Heslington, York, UK and Department of Computer Science;York Centre for Complex Systems Analysis, University of York, Heslington, York, UK and Department of Computer Science;York Centre for Complex Systems Analysis, University of York, Heslington, York, UK and Department of Electronics;York Centre for Complex Systems Analysis, University of York, Heslington, York, UK and Department of Biology

  • Venue:
  • CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
  • Year:
  • 2009

  • Molecular microprograms

    ECAL'09 Proceedings of the 10th European conference on Advances in artificial life: Darwin meets von Neumann - Volume Part I

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Abstract

The bacterial genome is well understood by biologists. Although its efficiency and adaptability should make it a good model for evolutionary algorithms, the bacterial genome is tightly coupled with the components of the bacterial metabolism, referred to here as the metabolome. This paper explores an approach to modelling an artificial bacterial metabolome in an efficient and modular manner, so that analogues of bacterial genome organisation and gene regulation can be implemented in evolutionary algorithms. We propose a particulate model of bacterial metabolic pathways in which the constituents drift in a fixed, limited space and obey a limited set of biologically plausible reaction rules. The potential of this model is demonstrated by creating a network that is capable of appropriate behavioural switching that can be observed in bacteria.