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Comparative and Functional Genomics
Volume 5, Issue 1, Pages 100-104
Conference review

Individual-Based Modelling of Bacterial Ecologies and Evolution

1BioComputing and Computational Biology Research Group, Department of Computer Science, University of Liverpool, Chadwick Building, Peach Street, Liverpool L69 7ZF, UK
2Department of Electrical Engineering and Electronics, Faculty of Engineering, University of Liverpool, Brownlow Hill, Liverpool L69 3GJ, UK
3Microbiology and Genomics Division, School of Biological Sciences, University of Liverpool, Biosciences Building, Liverpool L69 7ZB, UK

Received 17 November 2003; Revised 18 November 2003; Accepted 27 November 2003

Copyright © 2004 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper presents two approaches to the individual-based modelling of bacterial ecologies and evolution using computational tools. The first approach is a fine-grained model that is based on networks of interactivity between computational objects representing genes and proteins. The second approach is a coarser-grained, agent-based model, which is designed to explore the evolvability of adaptive behavioural strategies in artificial bacteria represented by learning classifier systems. The structure and implementation of these computational models is discussed, and some results from simulation experiments are presented. Finally, the potential applications of the proposed models to the solution of real-world computational problems, and their use in improving our understanding of the mechanisms of evolution, are briefly outlined.