ArticleBioinformatics advances2025
pastboon: an R package to simulate parameterized stochastic Boolean networks.
Article in Bioinformatics advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
3 authors.
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Abstract
Summary: Influencing the behavior of a Boolean network involves applying perturbations, which, in standard deterministic Boolean networks, is equivalent to modifying the update rules. Nevertheless, manipulating update functions to make a Boolean network exhibit the desired dynamics is challenging, as it requires extensive knowledge of the rationale behind the logical equations. Moreover, modifying logical rules can inadvertently alter essential functional and behavioral characteristics of the network. An alternative approach is to incorporate a set of parameters into the logical functions of Boolean networks. With such methods, one can alter the behavior of the network without needing detailed knowledge of the logical functions. We developed pastboon, an R package to simulate parameterized stochastic Boolean networks using three parameterization methods. This package enables researchers to study the phenotypic effects of various perturbations on Boolean network models describing cellular processes, which find valuable applications in systems biology. Availability and implementation: pastboon is freely available on the R CRAN repository at https://cran.r-project.org/package=pastboon, and its source code can be accessed on GitHub at https://github.com/taherimo/pastboon.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.