The tool mpbn offers a Python programming interface for an easy interactive editing of Boolean networks and the efficient computation of elementary properties of their dynamics, including fixed points, trap spaces, and reachability properties under the Most Permissive update mode. Relying on Answer-Set Programming logical framework, we show that mpbn is scalable to models with several thousands of nodes and is one of the best-performing tool for computing minimal and maximal trap spaces of Boolean networks, a key feature for understanding and controling their stable behaviors. The tool is available at https://github.com/bnediction/mpbn.

翻译：工具mpbn提供了一个Python编程接口，便于交互式编辑布尔网络并高效计算其动态特性的基本属性，包括不动点、陷阱空间以及最容许更新模式下的可达性属性。基于答案集编程逻辑框架，我们证明mpbn可扩展至数千节点的模型，并且在计算布尔网络的最小与最大陷阱空间方面性能最优——这是理解与控制其稳定行为的关键功能。该工具可通过https://github.com/bnediction/mpbn获取。