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A fundamental premise of statistical physics is that the particles in a physical system are interchangeable, and hence the state of each specific component is representative of the system as a whole. This assumption breaks down for complex…

Physics and Society · Physics 2025-12-16 Neil G. MacLaren , Baruch Barzel , Naoki Masuda

Interactions between genes and gene products give rise to complex circuits that enable cells to process information and respond to external signals. Theoretical studies often describe these interactions using continuous, stochastic, or…

Molecular Networks · Quantitative Biology 2007-05-23 Madalena Chaves , Reka Albert , Eduardo D. Sontag

Complex network theory provides a unifying framework for the study of structured dynamic systems. The current literature emphasizes a widely reported phenomenon of intermittent interaction among network vertices. In this paper, we introduce…

Social and Information Networks · Computer Science 2025-02-17 Ziyan Zeng , Minyu Feng , Pengfei Liu , Jurgen Kurths

Boolean networks may be viewed as idealizations of biological genetic networks, where each node is represented by an on-off switch which is a function of the binary output from some other nodes. We evolve connectivity in a single Boolean…

Biological Physics · Physics 2016-09-08 Stefan Bornholdt , Kim Sneppen

Estimating dependence relationships between variables is a crucial issue in many applied domains, such as medicine, social sciences and psychology. When several variables are entertained, these can be organized into a network which encodes…

Methodology · Statistics 2025-01-01 Federico Castelletti

Canalization is a key organizing principle in complex systems, particularly in gene regulatory networks. It describes how certain input variables exert dominant control over a function's output, thereby imposing hierarchical structure and…

Discrete Mathematics · Computer Science 2025-10-31 Claus Kadelka

The dynamic stability of the Boolean networks representing a model for the gene transcriptional regulation (Kauffman model) is studied by calculating analytically and numerically the Hamming distance between two evolving configurations.…

Statistical Mechanics · Physics 2008-09-19 Deok-Sun Lee , Heiko Rieger

Gene regulatory networks (GRNs) play a central role in cellular decision-making. Understanding their structure and how it impacts their dynamics constitutes thus a fundamental biological question. GRNs are frequently modeled as Boolean…

Molecular Networks · Quantitative Biology 2024-01-19 Claus Kadelka , Taras-Michael Butrie , Evan Hilton , Jack Kinseth , Addison Schmidt , Haris Serdarevic

Boolean circuit is a computational graph that consists of the dynamic directed graph structure and static functionality. The commonly used logic optimization and Boolean matching-based transformation can change the behavior of the Boolean…

Machine Learning · Computer Science 2024-11-19 Liwei Ni , Xinquan Li , Biwei Xie , Huawei Li

Recent studies have investigated various dynamic processes characterizing collective behaviors in real-world systems. However, these dynamics have been studied individually in specific contexts. In this article, we present a holistic…

Applied Physics · Physics 2025-01-28 Ming Xie , Shibo He , Aming Li , Zike Zhang , Youxian Sun , Jiming Chen

Coregulation of the expression of groups of genes has been extensively demonstrated empirically in bacterial and eukaryotic systems. Such coregulation can arise through the use of shared regulatory motifs, which allow the coordinated…

Machine Learning · Statistics 2016-04-12 Jonathan H. Warrell , Musa M. Mhlanga

A central task in analyzing complex dynamics is to determine the loci of information storage and the communication topology of information flows within a system. Over the last decade and a half, diagnostics for the latter have come to be…

Statistical Mechanics · Physics 2016-06-20 Ryan G. James , Nix Barnett , James P. Crutchfield

Empirical evidence has revealed that biological regulatory systems are controlled by high-level coordination between topology and Boolean rules. In this study, we study the joint effects of degree and Boolean functions on the stability of…

Adaptation and Self-Organizing Systems · Physics 2021-03-12 Byungjoon Min

In complex systems, information propagation can be defined as diffused or delocalized, weakly localized, and strongly localized. This study investigates the application of graph neural network models to learn the behavior of a linear…

Machine Learning · Computer Science 2025-09-09 Priodyuti Pradhan , Amit Reza

Pinning control on complex dynamical networks has emerged as a very important topic in recent trends of control theory due to the extensive study of collective coupled behaviors and their role in physics, engineering and biology. In…

Optimization and Control · Mathematics 2016-01-25 Stephane Chretien , Sebastien Darses

The abundance of data affords researchers to pursue more powerful computational tools to learn the dynamics of complex system, such as neural networks, engineered systems and social networks. Traditional machine learning approaches capture…

Machine Learning · Computer Science 2024-05-16 Yan Shen , Fan Yang , Mingchen Gao , Wen Dong

Percolation in complex networks is viewed as both: a process that mimics network degradation and a tool that reveals peculiarities of the underlying network structure. During the course of percolation, networks undergo non-trivial…

Physics and Society · Physics 2019-02-05 Ivan Kryven

Canalization is a classic concept in Developmental Biology that is thought to be an important feature of evolving systems. In a Boolean network it is a form of network robustness in which a subset of the input signals control the behavior…

Molecular Networks · Quantitative Biology 2015-05-28 Matthew D. Reichl , Kevin E. Bassler

We propose new activity-dependent adaptive Boolean networks inspired by the cis-regulatory mechanism in gene regulatory networks. We analytically show that our model can be solved for stationary in-degree distribution for a wide class of…

Adaptation and Self-Organizing Systems · Physics 2017-12-08 Taichi Haruna

What can we learn about controlling a system solely from its underlying network structure? Here we adapt a recently developed framework for control of networks governed by a broad class of nonlinear dynamics that includes the major dynamic…

Disordered Systems and Neural Networks · Physics 2017-07-07 Jorge G. T. Zañudo , Gang Yang , Réka Albert