Reliability of genetic networks is evolvable

Abstract

Control of the living cell functions with remarkable reliability despite the stochastic nature of the underlying molecular networks -- a property presumably optimized by biological evolution. We here ask to what extent the property of a stochastic dynamical network to produce reliable dynamics is an evolvable trait. Using an evolutionary algorithm based on a deterministic selection criterion for the reliability of dynamical attractors, we evolve dynamical networks of noisy discrete threshold nodes. We find that, starting from any random network, reliability of the attractor landscape can often be achieved with only few small changes to the network structure. Further, the evolvability of networks towards reliable dynamics while retaining their function is investigated and a high success rate is found.

5 pages, 3 figures

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• The Yeast Cell-Cycle Network Is Robustly Designed
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• The dynamics of critical Kauffman networks under asynchronous stochastic update
• Neutral Mutations and Punctuated Equilibrium in Evolving Genetic Networks
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Cited by in corpus (9)

• Network evolution towards optimal dynamical performance
• Quantifying evolvability in small biological networks
• Boolean Networks Design by Genetic Algorithms
• Design of endurable networks in the presence of aging
• Symmetry-based coarse-graining of evolved dynamical networks
• Canalization in the Critical States of Highly Connected Networks of Competing Boolean Nodes
• Robust Regulatory Networks
• Boolean network robotics: a proof of concept
• Predicting attractors from spectral properties of stylized gene regulatory networks