Taming Asynchrony for Attractor Detection in Large Boolean Networks (Technical Report)

TL;DR

This paper introduces a novel SCC-based decomposition method to efficiently identify all attractors in large asynchronous Boolean networks, overcoming the state-space explosion problem common in biological system modeling.

Contribution

The paper presents a new decomposition approach that improves attractor detection in large Boolean networks, with proven correctness and demonstrated efficiency on real biological data.

Findings

Method successfully detects attractors in large networks

Proven correctness of the SCC-based decomposition

Efficient performance on real biological networks

Abstract

Boolean networks is a well-established formalism for modelling biological systems. A vital challenge for analysing a Boolean network is to identify all the attractors. This becomes more challenging for large asynchronous Boolean networks, due to the asynchronous updating scheme. Existing methods are prohibited due to the well-known state-space explosion problem in large Boolean networks. In this paper, we tackle this challenge by proposing a SCC-based decomposition method. We prove the correctness of our proposed method and demonstrate its efficiency with two real-life biological networks.