Gene regulation in a particle metabolome

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.

• Type: Conference
• Year: 2009
• Where: CEC
• Authors: Simon J. Hickinbotham, Edward Clark, Susan Stepney, Tim Clarke, Peter Young
• Keywords: Artificial Intelligence, Bacterial Genome, Bacterial Genome Organisation, CEC 2009, Evolutionary Algorithms