Emergent properties of gene regulatory networks: Models and data

Abstract

We emphasize here the importance of generic models of biological systems that aim at describing the features that are common to a wide class of systems, instead of studying in detail a specific subsystem in a specific cell type or organism. Among generic models of gene regulatory networks, Random Boolean networks (RBNs) are reviewed in depth, and it is shown that they can accurately describe some important experimental data, in particular the statistical properties of the perturbations of gene expression levels induced by the knock-out of a single gene. It is also shown that this kind of study may shed light on a candidate general dynamical property of biological systems. Several biologically plausible modifications of the original model are reviewed and discussed, and it is also show how RBNs can be applied to describe cell differentiation.