Simulation of Parameterized Stochastic Boolean Networks R package pastboon version 0.1.4 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. Software Depends: R (>= 3.5.0) Suggests: BoolNet Mohammad Taheri-Ledari <mo.taheri@ut.ac.ir> Comprehensive R Archive Network (CRAN) Mohammad Taheri-Ledari [aut, cre, cph] (ORCID: <https://orcid.org/0009-0007-9132-077X>), Kaveh Kavousi [ctb] (ORCID: <https://orcid.org/0000-0002-1906-3912>), Sayed-Amir Marashi [ctb] (ORCID: <https://orcid.org/0000-0001-9801-7449>), Authors of BoolNet [ctb] (Original authors of the BoolNet package), Troy D. Hanson [ctb] (Contributed uthash macros) Artistic-2.0 2025-01-24 application/tgz https://CRAN.R-project.org/package=pastboon doi:10.32614/CRAN.package.pastboon