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pastboon  

Simulation of Parameterized Stochastic Boolean Networks
View on CRAN: Click here


Download and install pastboon package within the R console
Install from CRAN:
install.packages("pastboon")

Install from Github:
library("remotes")
install_github("cran/pastboon")

Install by package version:
library("remotes")
install_version("pastboon", "0.1.4")



Attach the package and use:
library("pastboon")
Maintained by
Mohammad Taheri-Ledari
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-07-23
Latest Update: 2025-01-24
Description:
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: BNp (Boolean network with perturbations), described by Trairatphisan et al. (2013) <doi:10.1186/1478-811X-11-46>, SDDS (stochastic discrete dynamical systems), proposed by Murrugarra et al. (2012) <doi:10.1186/1687-4153-2012-5>, and PEW (Boolean network with probabilistic edge weights), 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.
How to cite:
Mohammad Taheri-Ledari (2024). pastboon: Simulation of Parameterized Stochastic Boolean Networks. R package version 0.1.4, https://cran.r-project.org/web/packages/pastboon. Accessed 07 Mar. 2026.
Previous versions and publish date:
0.1.0 (2024-07-23 02:30), 0.1.1 (2024-08-19 00:20), 0.1.2 (2024-08-22 10:50), 0.1.3 (2025-01-08 09:30)
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Complete documentation for pastboon
Functions, R codes and Examples using the pastboon R package
Full pastboon package functions and examples
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