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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,…

Molecular Networks · Quantitative Biology 2017-06-14 Andrzej Mizera , Jun Pang , Hongyang Qu , Qixia Yuan

This paper addresses the problem of finding cycles in the state transition graphs of synchronous Boolean networks. Synchronous Boolean networks are a class of deterministic finite state machines which are used for the modeling of gene…

Molecular Networks · Quantitative Biology 2009-01-29 Elena Dubrova , Maxim Teslenko

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…

Discrete Mathematics · Computer Science 2024-03-29 Elisa Tonello , Loïc Paulevé

Despite their apparent simplicity, random Boolean networks display a rich variety of dynamical behaviors. Much work has been focused on the properties and abundance of attractors. We here derive an expression for the number of attractors in…

Molecular Networks · Quantitative Biology 2007-05-23 Björn Samuelsson , Carl Troein

Despite their apparent simplicity, random Boolean networks display a rich variety of dynamical behaviors. Much work has been focused on the properties and abundance of attractors. The topologies of random Boolean networks with one input per…

Disordered Systems and Neural Networks · Physics 2009-11-11 Björn Samuelsson , Carl Troein

The structure of the graph defined by the interactions in a Boolean network can determine properties of the asymptotic dynamics. For instance, considering the asynchronous dynamics, the absence of positive cycles guarantees the existence of…

Discrete Mathematics · Computer Science 2022-06-24 Adrien Richard , Elisa Tonello

Boolean networks have been used in a variety of settings, as models for general complex systems as well as models of specific systems in diverse fields, such as biology, engineering, and computer science. Traditionally, their properties as…

Dynamical Systems · Mathematics 2024-02-02 Matthew Wheeler , Claus Kadelka , Alan Veliz-Cuba , David Murrugarra , Reinhard Laubenbacher

In previous works, we introduced the notion of dominant vertices in the context of dynamical systems on networks. This is a set of nodes in the underlying network whose evolution determines the whole network's dynamics after a transient…

Dynamical Systems · Mathematics 2026-03-05 Andrea España , William Funez , Edgardo Ugalde

Using analytic arguments, we show that dynamical attractor periods in large critical Boolean networks are power-law distributed. Our arguments are based on the method of relevant components, which focuses on the behavior of the nodes that…

Disordered Systems and Neural Networks · Physics 2009-11-16 Florian Greil , Kevin E. Bassler

To simplify the analysis of Boolean networks, a reduction in the number of components is often considered. A popular reduction method consists in eliminating components that are not autoregulated, using variable substitution. In this work,…

Discrete Mathematics · Computer Science 2024-03-27 Robert Schwieger , Elisa Tonello

Modules were introduced as an extension of Boolean automata networks. They have inputs which are used in the computation said modules perform, and can be used to wire modules with each other. In the present paper we extend this new…

Discrete Mathematics · Computer Science 2020-02-12 Kévin Perrot , Pacôme Perrotin , Sylvain Sené

This paper details a method for optimising the size of Boolean automata networks in order to compute their attractors under the parallel update schedule. This method relies on the formalism of modules introduced recently that allows for…

Logic in Computer Science · Computer Science 2020-07-21 Kévin Perrot , Pacôme Perrotin , Sylvain Sené

This review explains in a self-contained way the properties of random Boolean networks and their attractors, with a special focus on critical networks. Using small example networks, analytical calculations, phenomenological arguments, and…

Statistical Mechanics · Physics 2008-11-14 Barbara Drossel

This is the second paper of a series of two about the structural properties that influence the asymptotic dynamics of Random Boolean Networks. Here we study the functionally independent clusters in which the relevant elements, introduced…

Disordered Systems and Neural Networks · Physics 2009-10-30 U. Bastolla , G. Parisi

Given a Boolean network BN and a subset A of attractors of BN, we study the problem of identifying a minimal subset C of vertices of BN, such that the dynamics of BN can reach from a state s in any attractor As in A to any attractor At in A…

Systems and Control · Computer Science 2018-06-29 Soumya Paul , Jun Pang , Cui Su

We present a computational method for finding attractors (ergodic sets of states) of Boolean networks under asynchronous update. The approach is based on a systematic removal of state transitions to render the state transition graph…

Disordered Systems and Neural Networks · Physics 2010-08-24 Thomas Skodawessely , Konstantin Klemm

The relationship between the properties of a dynamical system and the structure of its defining equations has long been studied in many contexts. Here we study this problem for the class of conjunctive (resp. disjunctive) Boolean networks,…

Combinatorics · Mathematics 2008-05-13 Abdul Salam Jarrah , Reinhard Laubenbacher , Alan Veliz-Cuba

To model biological systems using networks, it is desirable to allow more than two levels of expression for the nodes and to allow the introduction of parameters. Various modeling and simulation methods addressing these needs using Boolean…

Molecular Networks · Quantitative Biology 2014-04-23 Yi Ming Zou

We study the stable attractors of a class of continuous dynamical systems that may be idealized as networks of Boolean elements, with the goal of determining which Boolean attractors, if any, are good approximations of the attractors of…

Molecular Networks · Quantitative Biology 2009-11-13 Johannes Norrell , Björn Samuelsson , Joshua E. S. Socolar

Stream graphs model highly dynamic networks in which nodes and/or links arrive and/or leave over time. Strongly connected components in stream graphs were defined recently, but no algorithm was provided to compute them. We present here…

Social and Information Networks · Computer Science 2021-09-03 Léo Rannou , Clémence Magnien , Matthieu Latapy
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