Perturbation in Genetic Regulatory Networks: Simulation and Experiments

Abstract

Random boolean networks (RBN) have been proposed more than thirty years ago as models of genetic regulatory networks. Recent studies on the perturbation in gene expression levels induced by the knock-out (i.e. silencing) of single genes have shown that simple RBN models give rise to a distribution of the size of the perturbations which is very similar in different model network realizations, and is also very similar to the one actually found in experimental data concerning a unicellular organism (S.cerevisiae). In this paper we present further results, based upon the same set of experiments, concerning the correlation between different perturbations. We compare actual data from S. cerevisiae with the results of simulations concerning RBN models with more than 6000 nodes, and comment on the usefulness and limitations of RBN models.