pastboon: Simulation of Parameterized Stochastic Boolean Networks
A Boolean network is a particular kind of discrete dynamical system where the variables are simple binary switches. Despite its simplicity, Boolean network modeling has been a successful method to describe the behavioral pattern of various phenomena. Applying stochastic noise to Boolean networks is a useful approach for representing the effects of various perturbing stimuli on complex systems. A number of methods have been developed to control noise effects on Boolean networks using parameters integrated into the update rules. This package provides functions to examine three such methods: Boolean network with perturbations (BNp), described by Trairatphisan et al. (2013) <doi:10.1186/1478-811X-11-46>, stochastic discrete dynamical systems (SDDS), proposed by Murrugarra et al. (2012) <doi:10.1186/1687-4153-2012-5>, and Boolean network with probabilistic edge weights (PEW), presented by Deritei et al. (2022) <doi:10.1371/journal.pcbi.1010536>. This package includes source code derived from the 'BoolNet' package, which is licensed under the Artistic License 2.0.
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[aut, cre,
cph],
Kaveh Kavousi