Entropy of complex relevant components of Boolean networks

Abstract

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.

8 pages, 6 figures

References in corpus (2)

• Scaling in a general class of critical random Boolean networks
• Relevant components in critical random Boolean networks

Cited by in corpus (2)

• Random sampling vs. exact enumeration of attractors in random Boolean networks
• Feedback topology and XOR-dynamics in Boolean networks with varying input structure