ID: 1104.4511

Motifs emerge from function in model gene regulatory networks

April 22, 2011

View on ArXiv
Z. Burda, A. Krzywicki, O. C. Martin, M. Zagorski
Quantitative Biology
Condensed Matter
Molecular Networks
Statistical Mechanics

Gene regulatory networks arise in all living cells, allowing the control of gene expression patterns. The study of their topology has revealed that certain subgraphs of interactions or "motifs" appear at anomalously high frequencies. We ask here whether this phenomenon may emerge because of the functions carried out by these networks. Given a framework for describing regulatory interactions and dynamics, we consider in the space of all regulatory networks those that have a prescribed function. Monte Carlo sampling is then used to determine how these functional networks lead to specific motif statistics in the interactions. In the case where the regulatory networks are constrained to exhibit multi-stability, we find a high frequency of gene pairs that are mutually inhibitory and self-activating. In contrast, networks constrained to have periodic gene expression patterns (mimicking for instance the cell cycle) have a high frequency of bifan-like motifs involving four genes with at least one activating and one inhibitory interaction.

Similar papers 1

Thomas M. A. Fink
Molecular Networks
Statistical Mechanics

Developing and maintaining life requires a lot of computation. This is done by gene regulatory networks. But we have little understanding of how this computation is organized. I show that there is a direct correspondence between the structural and functional building blocks of regulatory networks, which I call regulatory motifs. I derive a simple bound on the range of function that these motifs can perform, in terms of the local network structure. I prove that this range is a...

Probabilistic generation of random networks taking into account information on motifs occurrence

November 25, 2013

89% Match
Frederic Y. Bois, Ghislaine Gayraud
Quantitative Methods
Molecular Networks

Because of the huge number of graphs possible even with a small number of nodes, inference on network structure is known to be a challenging problem. Generating large random directed graphs with prescribed probabilities of occurrences of some meaningful patterns (motifs) is also difficult. We show how to generate such random graphs according to a formal probabilistic representation, using fast Markov chain Monte Carlo methods to sample them. As an illustration, we generate re...

Find SimilarView on arXiv

Generic Properties of Random Gene Regulatory Networks

April 21, 2014

88% Match
Zhiyuan Li, Simone Bianco, ... , Tang Chao
Molecular Networks

Modeling gene regulatory networks (GRNs) is an important topic in systems biology. Although there has been much work focusing on various specific systems, the generic behavior of GRNs with continuous variables is still elusive. In particular, it is not clear typically how attractors partition among the three types of orbits: steady state, periodic and chaotic, and how the dynamical properties change with network's topological characteristics. In this work, we first investigat...

Find SimilarView on arXiv

Gene regulatory and signalling networks exhibit distinct topological distributions of motifs

December 19, 2017

88% Match
Gustavo Rodrigues Ferreira, Helder Imoto Nakaya, Luciano da Fontoura Costa
Molecular Networks

The biological processes of cellular decision making and differentiation involve a plethora of signalling pathways and gene regulatory circuits. These networks, in their turn, exhibit a multitude of motifs playing crucial parts in regulating network activity. Here, we compare the topological placement of motifs in gene regulatory and signalling networks and find that it suggests different evolutionary strategies in motif distribution for distinct cellular subnetworks.

Find SimilarView on arXiv

Edge usage, motifs and regulatory logic for cell cycling genetic networks

January 19, 2013

87% Match
M. Zagorski, A. Krzywicki, O. C. Martin
Molecular Networks
Statistical Mechanics

The cell cycle is a tightly controlled process, yet its underlying genetic network shows marked differences across species. Which of the associated structural features follow solely from the ability to impose the appropriate gene expression patterns? We tackle this question in silico by examining the ensemble of all regulatory networks which satisfy the constraint of producing a given sequence of gene expressions. We focus on three cell cycle profiles coming from baker's yeas...

Find SimilarView on arXiv

An algorithm for motif-based network design

May 13, 2016

87% Match
Tuomo Mäki-Marttunen
Social and Information Netwo...
Physics and Society

A determinant property of the structure of a biological network is the distribution of local connectivity patterns, i.e., network motifs. In this work, a method for creating directed, unweighted networks while promoting a certain combination of motifs is presented. This motif-based network algorithm starts with an empty graph and randomly connects the nodes by advancing or discouraging the formation of chosen motifs. The in- or out-degree distribution of the generated network...

Find SimilarView on arXiv

A statistical method for revealing form-function relations in biological networks

November 30, 2010

87% Match
Andrew Mugler, Boris Grinshpun, ... , Wiggins Chris H.
Molecular Networks
Quantitative Methods

Over the past decade, a number of researchers in systems biology have sought to relate the function of biological systems to their network-level descriptions -- lists of the most important players and the pairwise interactions between them. Both for large networks (in which statistical analysis is often framed in terms of the abundance of repeated small subgraphs) and for small networks which can be analyzed in greater detail (or even synthesized in vivo and subjected to expe...

Find SimilarView on arXiv

Network motifs emerge from interconnections that favor stability

November 20, 2014

86% Match
Marco Tulio Angulo, Yang-Yu Liu, Jean-Jacques Slotine
Systems and Control
Biological Physics
Physics and Society

Network motifs are overrepresented interconnection patterns found in real-world networks. What functional advantages may they offer for building complex systems? We show that most network motifs emerge from interconnections patterns that best exploit the intrinsic stability characteristics of individual nodes. This feature is observed at different scales in a network, from nodes to modules, suggesting an efficient mechanism to stably build complex systems.

Find SimilarView on arXiv

Counting Subnetworks Under Gene Duplication in Genetic Regulatory Networks

May 6, 2024

86% Match
Ashley Scruse, Jonathan Arnold, Robert Robinson
Molecular Networks
Combinatorics

Gene duplication is a fundamental evolutionary mechanism that contributes to biological complexity and diversity (Fortna et al., 2004). Traditionally, research has focused on the duplication of gene sequences (Zhang, 1914). However, evidence suggests that the duplication of regulatory elements may also play a significant role in the evolution of genomic functions (Teichmann and Babu, 2004; Hallin and Landry, 2019). In this work, the evolution of regulatory relationships belon...

Find SimilarView on arXiv

Dynamical Motifs: Building Blocks of Complex Network Dynamics

November 13, 2003

86% Match
Valentin P. Zhigulin
Disordered Systems and Neura...
Chaotic Dynamics
Neurons and Cognition

Spatio-temporal network dynamics is an emergent property of many complex systems which remains poorly understood. We suggest a new approach to its study based on the analysis of dynamical motifs -- small subnetworks with periodic and chaotic dynamics. We simulate randomly connected neural networks and, with increasing density of connections, observe the transition from quiescence to periodic and chaotic dynamics. We explain this transition by the appearance of dynamical motif...

Find SimilarView on arXiv