Artificial reaction networks

Claire Gerrard, John McCall, George MacLeod Coghill, Chris Macleod

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

6 Citations (Scopus)

Abstract

In this paper we present a novel method of simulating cellular intelligence, the Artificial Reaction Network (ARN). The ARN can be described as a modular S System, with some properties in common with other Systems Biology and AI techniques, including Random Boolean Networks, Petri Nets, Artificial Biochemical Networks and Artificial Neural Networks. We validate the ARN against standard biological data, and successfully apply it to simulate cellular intelligence associated with the well characterized cell signaling network of Escherichia coli chemotaxis. Finally, we explore the adaptability of the ARN, as a means to develop novel AI techniques, by successfully applying the simulated E. coli chemotaxis to a general optimization problem.
Original languageEnglish
Title of host publicationProceedings of the 11th UK Workshop on Computational Intelligence (UKCI 2011)
Place of PublicationManchester, UK
PublisherUniversity of Manchester
Pages20-25
Number of pages6
Publication statusPublished - Sep 2011
Event11th UK Workshop on Computational Intelligence - Manchester, United Kingdom
Duration: 7 Sep 20119 Sep 2011

Conference

Conference11th UK Workshop on Computational Intelligence
Country/TerritoryUnited Kingdom
CityManchester
Period7/09/119/09/11

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