Attractor identification in asynchronous Boolean dynamics with network reduction

TL;DR

This paper presents a novel method for identifying asynchronous cyclic attractors in Boolean networks by simplifying networks through component elimination, enabling faster analysis of biological and benchmark models.

Contribution

It introduces a new approach combining network reduction and reachability analysis for efficient attractor detection in Boolean models.

Findings

Significantly reduces computation time for attractor identification.

Effective on biological and random benchmark networks.

Combines established techniques in a novel way.

Abstract

Identification of attractors, that is, stable states and sustained oscillations, is an important step in the analysis of Boolean models and exploration of potential variants. We describe an approach to the search for asynchronous cyclic attractors of Boolean networks that exploits, in a novel way, the established technique of elimination of components. Computation of attractors of simplified networks allows the identification of a limited number of candidate attractor states, which are then screened with techniques of reachability analysis combined with trap space computation. An implementation that brings together recently developed Boolean network analysis tools, tested on biological models and random benchmark networks, shows the potential to significantly reduce running times.