Mohammad Taheri-Ledari, Sayed-Amir Marashi, Kaveh Kavousi
{"title":"pastboon: an R package to simulate parameterized stochastic Boolean networks.","authors":"Mohammad Taheri-Ledari, Sayed-Amir Marashi, Kaveh Kavousi","doi":"10.1093/bioadv/vbaf017","DOIUrl":null,"url":null,"abstract":"<p><strong>Summary: </strong>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.</p><p><strong>Availability and implementation: </strong>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.</p>","PeriodicalId":72368,"journal":{"name":"Bioinformatics advances","volume":"5 1","pages":"vbaf017"},"PeriodicalIF":2.4000,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12007881/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bioinformatics advances","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/bioadv/vbaf017","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
引用次数: 0
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.