title: Diversity of temporal correlations between genes in models of noisy and noiseless gene networks.
abstract: Gene regulatory networks (GRNs) are parallel information processing systems, binding past events to future actions. Since cell types stably remain in restricted subsets of the possible states of the GRN, they are likely the dynamical attractors of the GRN. These attractors differ in which genes are active and in the amount of information propagating within the network. Using mutual information (I) as a measure of information propagation between genes in a GRN, modeled as finite-sized Random Boolean Networks (RBN), we study how the dynamical regime of the GRN affects I within attractors (I(A)). The spectra of I(A) of individual RBNs are found to be scattered and diverse, and distributions of I(A) of ensembles are non-trivial and change shape with mean connectivity. Mean and diversity of I(A) values maximize in the chaotic near-critical regime, whereas ordered near-critical networks are the best at retaining the distinctiveness of each attractor's I(A) with noise. The results suggest that selection likely favors near-critical GRNs as these both maximize mean and diversity of I(A), and are the most robust to noise. We find similar I(A) distributions in delayed stochastic models of GRNs. For a particular stochastic GRN, we show that both mean and variance of I(A) have local maxima as its connectivity and noise levels are varied, suggesting that the conclusions for the Boolean network models may be generalizable to more realistic models of GRNs.
authors.affiliation: CSB Research Group, Dept. Signal Processing, Tampere Univ. Technology, Tampere, Finland. andre.sanchesribeiro@tut.fi
authors.forename: Andre S
authors.initials: AS
authors.lastname: Ribeiro
authors.forename: Jason
authors.initials: J
authors.lastname: Lloyd-Price
authors.forename: Sharif
authors.initials: S
authors.lastname: Chowdhury
authors.forename: Olli
authors.initials: O
authors.lastname: Yli-Harja
mesh_terms: D000465:Algorithms; D000818:Animals; D002450:Cell Communication / Q000235:genetics; D019295:Computational Biology / Q000379:methods; D003198:Computer Simulation; D005786:Gene Expression Regulation; D053263:Gene Regulatory Networks / Q000235:genetics*; D014644:Genetic Variation; D006801:Humans; D008957:Models, Genetic; D013269:Stochastic Processes