An Algorithm for Detecting Fixed Points of Boolean Networks

TL;DR

This paper introduces a new, straightforward algorithm for detecting fixed points in large Boolean networks by decomposing the problem into solvable subsystems, overcoming previous limitations and demonstrating effectiveness on sizable networks.

Contribution

The paper presents a novel approach that reduces the fixed point detection problem to solving smaller subsystems, independent of existing algorithms, enabling analysis of larger networks.

Findings

Successfully computed fixed points for networks with hundreds of nodes

Method is straightforward and easy to implement

Effective on large-scale Boolean networks

Abstract

In the applications of Boolean networks to modeling biological systems, an important computational problem is the detection of the fixed points of these networks. This is an NP-complete problem in general. There have been various attempts to develop algorithms to address the computation need for large size Boolean networks. The existing methods are usually based on known algorithms and thus limited to the situations where these known algorithms can apply. In this paper, we propose a novel approach to this problem. We show that any system of Boolean equations is equivalent to one Boolean equation, and thus it is possible to divide the polynomial equation system which defines the fixed points of a Boolean network into subsystems that can be solved easily. After solving these subsystems and thus reducing the number of states, we can combine the solutions to obtain all fixed points of the given network. This approach does not depend on other algorithms and it is straightforward and easy to implement. We show that our method can handle large size Boolean networks, and demonstrate its effectiveness by using MAPLE to compute the fixed points of Boolean networks with hundreds of nodes and thousands of interactions.