Regulatory Dynamics on Random Networks: Asymptotic Periodicity and Modularity

Abstract

We study the dynamics of discrete-time regulatory networks on random digraphs. For this we define ensembles of deterministic orbits of random regulatory networks, and introduce some statistical indicators related to the long-term dynamics of the system. We prove that, in a random regulatory network, initial conditions converge almost surely to a periodic attractor. We study the subnetworks, which we call modules, where the periodic asymptotic oscillations are concentrated. We proof that those modules are dynamically equivalent to independent regulatory networks.

23 pages, 3 figures

References in corpus (1)

• Scale-Free topologies and Activatory-Inhibitory interactions

Cited by in corpus (1)

• Dominant Vertices in Regulatory Networks Dynamics