Reliability of regulatory networks and its evolution

TL;DR

This paper investigates the reliability of biological regulatory networks' dynamics using a generalized Boolean model with noise, exploring how network evolution can enhance reliability while maintaining function.

Contribution

It introduces an evolutionary approach to improve the reliability of regulatory network dynamics without losing their original function.

Findings

Most networks can be evolved to achieve reliable dynamics.

Network structure significantly influences reliability.

Reliability can be improved through simple evolutionary processes.

Abstract

The problem of reliability of the dynamics in biological regulatory networks is studied in the framework of a generalized Boolean network model with continuous timing and noise. Using well-known artificial genetic networks such as the repressilator, we discuss concepts of reliability of rhythmic attractors. In a simple evolution process we investigate how overall network structure affects the reliability of the dynamics. In the course of the evolution, networks are selected for reliable dynamics. We find that most networks can be easily evolved towards reliable functioning while preserving the original function.