Evolution of Canalizing Boolean Networks

Abstract

Boolean networks with canalizing functions are used to model gene regulatory networks. In order to learn how such networks may behave under evolutionary forces, we simulate the evolution of a single Boolean network by means of an adaptive walk, which allows us to explore the fitness landscape. Mutations change the connections and the functions of the nodes. Our fitness criterion is the robustness of the dynamical attractors against small perturbations. We find that with this fitness criterion the global maximum is always reached and that there is a huge neutral space of 100% fitness. Furthermore, in spite of having such a high degree of robustness, the evolved networks still share many features with "chaotic" networks.

8 pages, 10 figures; revised and extended version

References in corpus (5)

• The Yeast Cell-Cycle Network Is Robustly Designed
• Random Boolean Network Models and the Yeast Transcriptional Network
• Genetic networks with canalyzing Boolean rules are always stable
• Canalizing Kauffman networks: non-ergodicity and its effect on their critical behavior
• Emergent Criticality from Co-evolution in Random Boolean Networks

Cited by in corpus (13)

• Chaotic Gene Regulatory Networks Can Be Robust Against Mutations and Noise
• Perturbation propagation in random and evolved Boolean networks
• Emergence of robustness against noise: A structural phase transition in evolved models of gene regulatory networks
• The Emergence of Canalization and Evolvability in an Open-Ended, Interactive Evolutionary System
• Evolution of a population of random Boolean networks
• Reliability of genetic networks is evolvable
• Self-organization of heterogeneous topology and symmetry breaking in networks with adaptive thresholds and rewiring
• Boolean networks with robust and reliable trajectories
• Robustness Leads Close to the Edge of Chaos in Coupled Map Networks: toward the understanding of biological networks
• Time-evolution of the Rule 150 cellular automaton activity from a Fibonacci iteration
• Evolution of regulatory networks towards adaptability and stability in a changing environment
• Response of Boolean networks to perturbations
• Canalization in the Critical States of Highly Connected Networks of Competing Boolean Nodes