pastboon: an R package to simulate parameterized stochastic Boolean networks.

IF 2.4 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Bioinformatics advances Pub Date : 2025-02-06 eCollection Date: 2025-01-01 DOI:10.1093/bioadv/vbaf017
Mohammad Taheri-Ledari, Sayed-Amir Marashi, Kaveh Kavousi
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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.

一个R包来模拟参数化的随机布尔网络。
摘要:影响布尔网络的行为涉及应用摄动,在标准确定性布尔网络中,摄动相当于修改更新规则。然而,操作更新函数以使布尔网络显示所需的动态是具有挑战性的,因为它需要对逻辑方程背后的基本原理有广泛的了解。此外,修改逻辑规则可能会无意中改变网络的基本功能和行为特征。另一种方法是将一组参数合并到布尔网络的逻辑函数中。有了这样的方法,人们可以改变网络的行为,而不需要详细了解逻辑功能。我们开发了pastboon,一个R包来模拟参数化随机布尔网络,使用三种参数化方法。该软件包使研究人员能够研究描述细胞过程的布尔网络模型上各种扰动的表型效应,这些模型在系统生物学中有价值的应用。可用性和实现:pastboon可以在R CRAN存储库中免费获得https://cran.r-project.org/package=pastboon,其源代码可以在GitHub上访问https://github.com/taherimo/pastboon。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
1.60
自引率
0.00%
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