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.
Version: |
0.1.4 |
Depends: |
R (≥ 3.5.0) |
Suggests: |
BoolNet |
Published: |
2025-01-24 |
Author: |
Mohammad Taheri-Ledari
[aut, cre,
cph] (<https://orcid.org/0009-0007-9132-077X>),
Kaveh Kavousi
[ctb] (<https://orcid.org/0000-0002-1906-3912>),
Sayed-Amir Marashi
[ctb]
(<https://orcid.org/0000-0001-9801-7449>),
Authors of BoolNet [ctb] (Original authors of the BoolNet package),
Troy D. Hanson [ctb] (Contributed uthash macros) |
Maintainer: |
Mohammad Taheri-Ledari <mo.taheri at ut.ac.ir> |
BugReports: |
https://github.com/taherimo/pastboon/issues |
License: |
Artistic-2.0 |
NeedsCompilation: |
yes |
CRAN checks: |
pastboon results |
Documentation:
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