Modeling evolution of Regulatory Networks in Artificial Organisms - Archive ouverte HAL
Communication Dans Un Congrès Année : 2007

Modeling evolution of Regulatory Networks in Artificial Organisms

Résumé

Regulatory networks are not randomly connected. They are modular, scale-free networks and some motifs distribution is clearly different from random distribution. However, the evolutionary causes and consequences of this specific connectivity are mainly unknown. In this paper we propose Raevol, an integrative model to study the evolution of regulatory networks. While most existing models consider direct evolution of the regulatory network, Raevol integrates a realistic genotype-phenotype mapping where the genome undergo mutations that indirectly modify the genetic network. Moreover, the organisms are selected at the phenotype level (which is produced by the genome via the regulation network). Thus, in Raevol, the network only indirectly evolve and it can only be selected if its activity influences the phenotype. We plan to use this model to better understand the network evolution and to study the influence of networks topology on evolution.
Fichier non déposé

Dates et versions

hal-01613768 , version 1 (10-10-2017)

Identifiants

Citer

Yolanda Sanchez-Dehesa, Guillaume Beslon, Jose Maria Pena. Modeling evolution of Regulatory Networks in Artificial Organisms. 3rd International Symposium on Computational Life Science CompLife'07, Oct 2007, Utrecht, Netherlands. pp.87-98, ⟨10.1063/1.2793407⟩. ⟨hal-01613768⟩
266 Consultations
0 Téléchargements

Altmetric

Partager

More