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.
- Version0.1.2
- R versionunknown
- LicenseArtistic-2.0
- Needs compilation?Yes
- Last release08/22/2024
Team
Mohammad Taheri-Ledari
Kaveh Kavousi
Show author detailsRolesContributorTroy D. Hanson
Show author detailsRolesContributorSayed-Amir Marashi
Authors of BoolNet
Show author detailsRolesContributor
Insights
Last 30 days
Last 365 days
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Suggests1 package