mpbn: a simple tool for efficient edition and analysis of elementary properties of Boolean networks

TL;DR

mpbn is a Python tool that enables easy editing and analysis of Boolean networks, efficiently computing key dynamic properties like fixed points and trap spaces, scalable to large models.

Contribution

Introduces mpbn, a scalable Python-based tool leveraging Answer-Set Programming for interactive editing and analysis of Boolean network dynamics.

Findings

Scalable to models with thousands of nodes

Efficient computation of trap spaces

One of the best-performing tools for fixed points and reachability

Abstract

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.