Modelling Evolution of Regulatory Networks in Artificial Bacteria

Yolanda Sanchez-Dehesa (1, 2) , David P. Parsons (1) , Jose Maria Pena (3) , Guillaume Beslon (2, 1)

1 DM2L - Data Mining and Machine Learning
2 IXXI - Institut Rhône-Alpin des systèmes complexes
3 DATSI - Departamento de Arquitectura y Tecnología de Sistemas Informáticos [Madrid]

Studying the evolutive and adaptative mechanisms of prokaryotes is a complicated task. As these mechanisms cannot be easily studied ``in vivo'', it is necessary to consider other methods. We have therefore developed the RAevol model, a model designed to study the evolution of bacteria and their adaptation to the environment. Our model simulates the evolution of a population of artificial bacteria in a changing environment, providing us with an insight into the strategies that digital organisms develop to adapt to new conditions. In this paper we describe the principles and architecture of the model, focusing on the mechanisms of the regulatory networks of artificial organisms. Experiments were conducted on populations of artificial bacteria under conditions of stress. We study the ways in which organisms adapt to environmental changes and examine the strategies they adopt. An analysis of these adaptation strategies is presented and a brief overview was proposed concerning the patterns and topological characteristics of the evolved regulatory networks.

Domaines: Informatique [cs]

Yolanda Sanchez-Dehesa, David P. Parsons, Jose Maria Pena, Guillaume Beslon. Modelling Evolution of Regulatory Networks in Artificial Bacteria. Mathematical Modelling of Natural Phenomena, 2008, 2, 3, pp.27-66. ⟨10.1051/mmnp:2008054⟩. ⟨hal-01500393⟩