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Chemical master equation plays an important role to describe the time evolution of homogeneous chemical system. In addition to the reaction process, it is also accompanied by physical diffusion of the reactants in complex system that is…

Chemical Physics · Physics 2025-03-06 Hong Zhang , Guohua Li

We present a simple and general framework to simulate statistically correct realizations of a system of non-Markovian discrete stochastic processes. We give the exact analytical solution and a practical an efficient algorithm alike the…

Disordered Systems and Neural Networks · Physics 2014-10-21 Marian Boguna , Luis F. Lafuerza , Raul Toral , M. Angeles Serrano

Continuous-time Markov chains are used to model stochastic systems where transitions can occur at irregular times, e.g., birth-death processes, chemical reaction networks, population dynamics, and gene regulatory networks. We develop a…

Machine Learning · Statistics 2022-12-13 Majerle Reeves , Harish S. Bhat

Models invoking the chemical master equation are used in many areas of science, and, hence, their simulation is of interest to many researchers. The complexity of the problems at hand often requires considerable computational power, so a…

Biological Physics · Physics 2016-03-02 Fabian Spill , Philip K. Maini , Helen Byrne

We propose a general stochastic formalism for describing the evolution of chemical reactions involving a finite number of molecules. This approach is consistent with the statistical analysis based on the Chemical Master Equation, and…

Statistical Mechanics · Physics 2023-01-13 Chiara Pezzotti , Massimiliano Giona

Discrete-state, continuous-time Markov models are becoming commonplace in the modelling of biochemical processes. The mathematical formulations that such models lead to are opaque, and, due to their complexity, are often considered…

Quantitative Methods · Quantitative Biology 2017-10-31 Christopher Lester

This article presents an algorithm that allows modeling of biological networks in a qualitative framework with continuous time. Mathematical modeling is used as a systems biology tool to answer biological questions, and more precisely, to…

Molecular Networks · Quantitative Biology 2012-05-30 Gautier Stoll , Eric Viara , Emmanuel Barillot , Laurence Calzone

Chemical reaction systems with a low to moderate number of molecules are typically modeled as discrete jump Markov processes. These systems are oftentimes simulated with methods that produce statistically exact sample paths such as the…

Molecular Networks · Quantitative Biology 2015-05-13 David F. Anderson

We consider a continuous-time random walk which is the generalization, by means of the introduction of waiting periods on sites, of the one-dimensional nonhomogeneous random walk with a position-dependent drift known in the mathematical…

Statistical Mechanics · Physics 2021-10-25 Gaia Pozzoli , Mattia Radice , Manuele Onofri , Roberto Artuso

The model of chemical reaction networks is among the oldest and most widely studied and used in natural science. The model describes reactions among abstract chemical species, for instance $A + B \to C$, which indicates that if a molecule…

Data Structures and Algorithms · Computer Science 2026-02-16 Joshua Petrack , David Doty

Simulating stochastic systems with feedback control is challenging due to the complex interplay between the system's dynamics and the feedback-dependent control protocols. We present a single-step-trajectory probability analysis to…

Statistical Mechanics · Physics 2024-12-19 Supraja S. Chittari , Zhiyue Lu

Enzyme kinetics has historically been described by deterministic models, with the Michaelis-Menten (MM) equation serving as a paradigm. However, recent experimental and theoretical advances have made it clear that stochastic fluctuations,…

Molecular Networks · Quantitative Biology 2025-04-08 Jiaji Qu , Malini Rajbhandari

In an experimental study of single enzyme reactions, it has been proposed that the rate constants of the enzymatic reactions fluctuate randomly, according to a given distribution. To quantify the uncertainty arising from random rate…

Quantitative Methods · Quantitative Biology 2012-02-07 Chia Ying Lee

The Gillespie algorithm provides statistically exact methods for simulating stochastic dynamics modelled as interacting sequences of discrete events including systems of biochemical reactions or earthquake occurrences, networks of queuing…

Physics and Society · Physics 2020-02-20 Naoki Masuda , Luis E. C. Rocha

We introduce a reaction-path statistical mechanics formalism based on the principle of large deviations to quantify the kinetics of single-molecule enzymatic reaction processes under the Michaelis-Menten mechanism, which exemplifies an…

Statistical Mechanics · Physics 2022-04-11 Hyuntae Lim , YounJoon Jung

We present a kinetic Monte Carlo method for simulating chemical transformations specified by reaction rules, which can be viewed as generators of chemical reactions, or equivalently, definitions of reaction classes. A rule identifies the…

Quantitative Methods · Quantitative Biology 2010-07-09 Jin Yang , Michael I. Monine , James R. Faeder , William S. Hlavacek

Stochastic reaction networks, which are usually modeled as continuous-time Markov chains on $\mathbb Z^d_{\ge 0}$, and simulated via a version of the "Gillespie algorithm," have proven to be a useful tool for the understanding of processes,…

Probability · Mathematics 2025-07-15 David F. Anderson , Aidan S. Howells

We formulate the generalized master equation for a class of continuous time random walks in the presence of a prescribed deterministic evolution between successive transitions. This formulation is exemplified by means of an…

Statistical Mechanics · Physics 2009-11-13 S. Eule , R. Friedrich , F. Jenko , I. M. Sokolov

Reaction-diffusion equations deliver a versatile tool for the description of reactions in inhomogeneous systems under the assumption that the characteristic reaction scales and the scales of the inhomogeneities in the reactant…

Statistical Mechanics · Physics 2009-11-11 M. G. W. Schmidt , F. Sagues , I. M. Sokolov

We present a study of the spatial correlation functions of a one-dimensional reaction-diffusion system in both equilibrium and out of equilibrium. For the numerical simulations we have employed the Gillespie algorithm dividing the system in…

Statistical Mechanics · Physics 2014-01-08 Jorge Luis Hita , José María Ortiz de Zárate
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