Boolean network models of strongly connected modules are capable of capturing the high regulatory complexity of many biological gene regulatory circuits. We study numerically the previously introduced basin entropy, a parameter for the dynamical uncertainty or information storage capacity of a network as well as the average transient time in random relevant components as a function of their connectivity. We also demonstrate that basin entropy can be estimated from time-series data and is therefore also applicable to non-deterministic networks models.
@article{arxiv.0708.1538,
title = {Entropy of complex relevant components of Boolean networks},
author = {P. Krawitz and I. Shmulevich},
journal= {arXiv preprint arXiv:0708.1538},
year = {2009}
}