Individual-based modelling of bacterial ecologies and evolution

Citations of this article
Mendeley users who have this article in their library.


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.




Vlachos, C., Gregory, R., Paton, R. C., Saunders, J. R., & Wu, Q. H. (2004). Individual-based modelling of bacterial ecologies and evolution. In Comparative and Functional Genomics (Vol. 5, pp. 100–104).

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free