title: 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 nondeterministic networks models.
authors.affiliation: Institute for Systems Biology, Seattle, Washington 98103, USA.
authors.forename: Peter
authors.initials: P
authors.lastname: Krawitz
authors.forename: Ilya
authors.initials: I
authors.lastname: Shmulevich
mesh_terms: D003198:Computer Simulation; D019277:Entropy; D005786:Gene Expression Regulation / Q000502:physiology*; D016015:Logistic Models; D008954:Models, Biological; D015233:Models, Statistical; D020543:Proteome / Q000378:metabolism*; D015398:Signal Transduction / Q000502:physiology*
chemical_list: D020543:Proteome