pystablemotifs：用于布尔网络吸引子识别和控制的 Python 库。
pystablemotifs: Python library for attractor identification and control in Boolean networks.
机构信息
Department of Physics, The Pennsylvania State University, University Park, PA 16802, USA.
Department of Molecular Biology, Semmelweis University, Budapest 1085, Hungary.
出版信息
Bioinformatics. 2022 Feb 7;38(5):1465-1466. doi: 10.1093/bioinformatics/btab825.
SUMMARY
pystablemotifs is a Python 3 library for analyzing Boolean networks. Its non-heuristic and exhaustive attractor identification algorithm was previously presented in Rozum et al. (2021). Here, we illustrate its performance improvements over similar methods and discuss how it uses outputs of the attractor identification process to drive a system to one of its attractors from any initial state. We implement six attractor control algorithms, five of which are new in this work. By design, these algorithms can return different control strategies, allowing for synergistic use. We also give a brief overview of the other tools implemented in pystablemotifs.
AVAILABILITY AND IMPLEMENTATION
The source code is on GitHub at https://github.com/jcrozum/pystablemotifs/.
SUPPLEMENTARY INFORMATION
Supplementary data are available at Bioinformatics online.
摘要
pystablemotifs 是一个用于分析布尔网络的 Python 3 库。Rozum 等人（2021）之前曾提出其非启发式和穷举吸引子识别算法。在这里，我们展示了它相对于类似方法的性能改进，并讨论了它如何利用吸引子识别过程的输出，从任何初始状态将系统驱动到其吸引子之一。我们实现了六个吸引子控制算法，其中有五个是这项工作中的新算法。通过设计，这些算法可以返回不同的控制策略，从而实现协同使用。我们还简要介绍了 pystablemotifs 中实现的其他工具。
可用性和实现
源代码可在 GitHub 上获得，网址为 https://github.com/jcrozum/pystablemotifs/。
补充信息
补充数据可在 Bioinformatics 在线获取。
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