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Reaction networks in the bulk and on surfaces are widespread in physical, chemical and biological systems. In macroscopic systems, which include large populations of reactive species, stochastic fluctuations are negligible and the reaction…

Statistical Mechanics · Physics 2007-10-12 Baruch Barzel , Ofer Biham , Raz Kupferman

The bulk of stochastic gene expression models in the literature do not have an explicit description of the age of a cell within a generation and hence they cannot capture events such as cell division and DNA replication. Instead, many…

Subcellular Processes · Quantitative Biology 2020-03-11 Casper H. L. Beentjes , Ruben Perez-Carrasco , Ramon Grima

We prove that nested canalizing functions are the minimum-sensitivity Boolean functions for any activity ratio and we determine the functional form of this boundary which has a nontrivial fractal structure. We further observe that the…

Molecular Networks · Quantitative Biology 2024-08-14 Hamza Coban

Many approaches to modelling reaction-diffusion systems with anomalous transport rely on deterministic equations and ignore fluctuations arising due to finite particle numbers. Starting from an individual-based model we use a…

Statistical Mechanics · Physics 2019-05-29 Joseph W. Baron , Tobias Galla

In this paper we consider deterministic limits of molecular stochastic systems with finite and infinite degrees of freedom. The method to obtain the deterministic vector field is based on the continuum limit of such microscopic systems…

Molecular Networks · Quantitative Biology 2008-02-29 L. Sbano , M. Kirkilionis

In this paper we investigate the normal and the large fluctuations of additive functionals associated with a stochastic process under a general non-Poissonian resetting mechanism. Cumulative functionals of regenerative processes are very…

Probability · Mathematics 2023-04-24 Marco Zamparo

We introduce a minimal model description for the dynamics of transcriptional regulatory networks. It is studied within a mean-field approximation, i.e., by deterministic ode's representing the reaction kinetics, and by stochastic…

Molecular Networks · Quantitative Biology 2009-11-13 R. Blossey , C. V. Giuraniuc

Living cells provide a fluctuating, out-of-equilibrium environment in which genes must coordinate cellular function. DNA looping, which is a common means of regulating transcription, is very much a stochastic process; the loops arise from…

Biomolecules · Quantitative Biology 2015-05-18 Yih-Fan Chen , J. N. Milstein , Jens-Christian Meiners

Understanding the interplay among processes that occur over different timescales is a challenging issue in the physics of systems regulation. In gene regulation, the timescales for changes in chromatin states can differ from those for…

Biological Physics · Physics 2025-07-01 Masaki Sasai , Bhaswati Bhattacharyya , Shin Fujishiro , Yoshiaki Horiike

Stochasticity is a key characteristic of intracellular processes such as gene regulation and chemical signalling. Therefore, characterising stochastic effects in biochemical systems is essential to understand the complex dynamics of living…

Molecular Networks · Quantitative Biology 2019-03-04 David J. Warne , Ruth E. Baker , Matthew J. Simpson

We consider the general problem of describing the dynamics of subnetworks of larger biochemical reaction networks, e.g. protein interaction networks involving complex formation and dissociation reactions. We propose the use of model…

Quantitative Methods · Quantitative Biology 2020-08-26 Barbara Bravi , Katy J. Rubin , Peter Sollich

Gene regulatory networks are typically modeled using ordinary differential equations (ODEs) with phenomenological Hill functions to represent transcriptional regulation. While computationally efficient, Hill functions lack mechanistic…

Molecular Networks · Quantitative Biology 2026-01-16 Tianyu Wu

Discrete gene regulatory networks (GRNs) play a vital role in the study of robustness and modularity. A common method of evaluating the robustness of GRNs is to measure their ability to regulate a set of perturbed gene activation patterns…

Neural and Evolutionary Computing · Computer Science 2021-12-14 Zhenyue Qin , Tom Gedeon , Bob McKay

A general class of stochastic gene expression models with self regulation is considered. One or more genes randomly switch between regulatory states, each having a different mRNA transcription rate. The gene or genes are self regulating…

Molecular Networks · Quantitative Biology 2014-12-30 Jay Newby

Synthetic biology is an interdisciplinary field aiming to design biochemical systems with desired behaviors. To this end, molecular controllers have been developed which, when embedded into a pre-existing ambient biochemical network,…

Molecular Networks · Quantitative Biology 2019-08-29 Tomislav Plesa , Guy-Bart Stan , Thomas E. Ouldridge , Wooli Bae

We present an algorithm for the stochastic simulation of gene expression and heterogeneous population dynamics. The algorithm combines an exact method to simulate molecular-level fluctuations in single cells and a constant-number Monte…

Computational Physics · Physics 2016-08-24 Daniel A. Charlebois , Jukka Intosalmi , Dawn Fraser , Mads Kaern

We consider the problem of estimating the dynamic latent states of an intracellular multiscale stochastic reaction network from time-course measurements of fluorescent reporters. We first prove that accurate solutions to the filtering…

Methodology · Statistics 2020-09-09 Zhou Fang , Ankit Gupta , Mustafa Khammash

A chain of connected genes with activation-repression links is analysed. It is shown that for various promoter activity functions (parametrised by Hill coefficient) the equations describing the concentrations of transcription factors, are…

Genomics · Quantitative Biology 2007-05-23 A. S. Carstea

We present a systematic mathematical analysis of the qualitative steady-state response to rate perturbations in large classes of reaction networks. This includes multimolecular reactions and allows for catalysis, enzymatic reactions,…

Dynamical Systems · Mathematics 2017-11-22 Bernhard Brehm , Bernold Fiedler

Assume that a stochastic processes can be approximated, when some scale parameter gets large, by a fluid limit (also called "mean field limit", or "hydrodynamic limit"). A common practice, often called the "fixed point approximation"…

Dynamical Systems · Mathematics 2022-06-28 Jean-Yves Le Boudec