PyBoolNet：一个用于布尔网络生成、分析和可视化的Python软件包。
PyBoolNet: a python package for the generation, analysis and visualization of boolean networks.
作者信息
Klarner Hannes, Streck Adam, Siebert Heike
出版信息
Bioinformatics. 2017 Mar 1;33(5):770-772. doi: 10.1093/bioinformatics/btw682.
MOTIVATION
The goal of this project is to provide a simple interface to working with Boolean networks. Emphasis is put on easy access to a large number of common tasks including the generation and manipulation of networks, attractor and basin computation, model checking and trap space computation, execution of established graph algorithms as well as graph drawing and layouts.
RESULTS
P y B ool N et is a Python package for working with Boolean networks that supports simple access to model checking via N u SMV, standard graph algorithms via N etwork X and visualization via dot . In addition, state of the art attractor computation exploiting P otassco ASP is implemented. The package is function-based and uses only native Python and N etwork X data types.
AVAILABILITY AND IMPLEMENTATION
https://github.com/hklarner/PyBoolNet.
CONTACT
动机
本项目的目标是提供一个用于处理布尔网络的简单接口。重点在于能够轻松访问大量常见任务，包括网络的生成与操作、吸引子和盆地计算、模型检查以及陷阱空间计算、执行既定的图算法以及图形绘制和布局。
结果
PyBoolNet是一个用于处理布尔网络的Python包，支持通过NuSMV进行简单的模型检查访问、通过NetworkX进行标准图算法访问以及通过dot进行可视化。此外，还实现了利用Potassco ASP的先进吸引子计算。该包基于函数，仅使用原生Python和NetworkX数据类型。
可用性与实现
https://github.com/hklarner/PyBoolNet。
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