Evolving Boolean Regulatory Networks with Variable Gene Expression Times

TL;DR

This paper investigates how variable gene expression times can evolve in Boolean regulatory networks, showing that non-uniform expression times can emerge as beneficial for network dynamics through simulated evolution.

Contribution

It introduces a tunable Boolean network model to demonstrate the emergence of variable gene expression times via evolution, highlighting their role in network behavior.

Findings

Non-uniform expression times can evolve under certain conditions.

Variable gene expression times influence network dynamics.

Evolution favors diverse gene expression durations.

Abstract

The time taken for gene expression varies not least because proteins vary in length considerably. This paper uses an abstract, tuneable Boolean regulatory network model to explore gene expression time variation. In particular, it is shown how non-uniform expression times can emerge under certain conditions through simulated evolution. That is, gene expression time variance appears beneficial in the shaping of the dynamical behaviour of the regulatory network without explicit consideration of protein function.