mpbn：一款用于高效编辑与分析布尔网络基本性质的简易工具
mpbn: a simple tool for efficient edition and analysis of elementary properties of Boolean networks
AI总结：
本研究推出工具mpbn，其提供Python接口支持布尔网络编辑与动力学性质计算，依托回答集编程框架可适配数千节点模型，在计算布尔网络最小/最大陷阱空间上性能优异，助力稳定行为的研究与调控。
摘要：
mpbn工具提供Python编程接口，可便捷交互式编辑布尔网络，并高效计算其动力学基本性质，包括Most Permissive（最宽松）更新模式下的不动点、陷阱空间及可达性性质。依托Answer-Set Programming（回答集编程）逻辑框架，我们证明mpbn可扩展至包含数千个节点的模型，且是计算布尔网络最小与最大陷阱空间的性能最优工具之一，该特性对理解和调控布尔网络的稳定行为至关重要。该工具可在https://github.com/bnediction/mpbn 获取。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
