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Reaction networks (RNs) comprise a set $X$ of species and a set $\mathscr{R}$ of reactions $Y\to Y'$, each converting a multiset of educts $Y\subseteq X$ into a multiset $Y'\subseteq X$ of products. RNs are equivalent to directed…

Molecular Networks · Quantitative Biology 2022-01-06 Stefan Müller , Christoph Flamm , Peter F. Stadler

A reaction network is a chemical system involving multiple reactions and chemical species. Stochastic models of such networks treat the system as a continuous time Markov chain on the number of molecules of each species with reactions as…

Probability · Mathematics 2007-05-23 Karen Ball , Thomas G. Kurtz , Lea Popovic , Greg Rempala

For the investigation of chemical reaction networks, the efficient and accurate determination of all relevant intermediates and elementary reactions is mandatory. The complexity of such a network may grow rapidly, in particular if reactive…

Chemical Physics · Physics 2016-01-08 Maike Bergeler , Gregor N. Simm , Jonny Proppe , Markus Reiher

Molecular computation based on chemical reaction networks (CRNs) has emerged as a promising paradigm for designing programmable biochemical systems. However, the implementation of complex computations still requires excessively large and…

Molecular Networks · Quantitative Biology 2025-06-17 Renlei Jiang , Yuzhen Fan , Di Fan , Chuanhou Gao , Denis Dochain

Chemical reactions that couple to systems that phase separate have been implicated in diverse contexts from biology to materials science. However, how a particular set of chemical reactions (chemical reaction network, CRN) would affect the…

Soft Condensed Matter · Physics 2024-04-25 Dino Osmanovic , Elisa Franco

We address a fundamental problem in chemistry known as chemical reaction product prediction. Our main insight is that the input reactant and reagent molecules can be jointly represented as a graph, and the process of generating product…

Neural and Evolutionary Computing · Computer Science 2018-12-27 Kien Do , Truyen Tran , Svetha Venkatesh

We present a novel method for identifying a biochemical reaction network based on multiple sets of estimated reaction rates in the corresponding reaction rate equations arriving from various (possibly different) experiments. The current…

Applications · Statistics 2008-10-06 Gheorghe Craciun , Casian Pantea , Grzegorz A. Rempala

Chemical reaction network theory is a powerful framework to describe and analyze chemical systems. While much about the concentration profile in an equilibrium state can be determined in terms of the graph structure, the overall reaction's…

Molecular Networks · Quantitative Biology 2024-02-29 Tomoharu Suda

Chemical reaction networks (CRNs) formally model chemistry in a well-mixed solution. CRNs are widely used to describe information processing occurring in natural cellular regulatory networks, and with upcoming advances in synthetic biology,…

Computational Complexity · Computer Science 2015-03-20 Ho-Lin Chen , David Doty , David Soloveichik

This paper studies the (discrete) \emph{chemical reaction network (CRN)} computational model that emerged in the last two decades as an abstraction for molecular programming. The correctness of CRN protocols is typically established under…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-07-04 Anne Condon , Yuval Emek , Noga Harlev

In this paper we study a class of stochastic chemical reaction networks (CRNs) for which chemical species are created by a sequence of chain reactions. We prove that under some convenient conditions on the initial state, some of these…

Probability · Mathematics 2024-06-19 Lucie Laurence , Philippe Robert

Chemical reaction networks, or CRNs, are known to stably compute semilinear Boolean-valued predicates and functions, provided that all reactions are irreversible. However, this property does not hold for wet-lab implementations, as all…

Computational Complexity · Computer Science 2026-04-17 Ravi Kini , David Doty

The asymptotic properties of some Markov processes associated to stochastic chemical reaction networks (CRNs) driven by the kinetics of the law of mass action are analyzed. The scaling regime introduced in the paper assumes that the norm of…

Probability · Mathematics 2025-12-18 Lucie Laurence , Philippe Robert

Reaction rates of chemical reactions under nonequilibrium conditions can be determined through the construction of the normally hyperbolic invariant manifold (NHIM) [and moving dividing surface (DS)] associated with the transition state…

Biochemical networks are used in computational biology, to model the static and dynamical details of systems involved in cell signaling, metabolism, and regulation of gene expression. Parametric and structural uncertainty, as well as…

Molecular Networks · Quantitative Biology 2014-10-15 Ovidiu Radulescu , Alexander N. Gorban , Andrei Zinovyev , Vincent Noel

Stochastic evolution of Chemical Reactions Networks (CRNs) over time is usually analysed through solving the Chemical Master Equation (CME) or performing extensive simulations. Analysing stochasticity is often needed, particularly when some…

Logic in Computer Science · Computer Science 2015-09-11 Luca Laurenti , Luca Cardelli , Marta Kwiatkowska

Cataloging the complex behaviors of dynamical systems can be challenging, even when they are well-described by a simple mechanistic model. If such a system is of limited analytical tractability, brute force simulation is often the only…

Machine Learning · Computer Science 2023-01-04 Hunter Elliott

Reaction networks are a general formalism for describing collections of classical entities interacting in a random way. While reaction networks are mainly studied by chemists, they are equivalent to Petri nets, which are used for similar…

Mathematical Physics · Physics 2021-11-23 John C. Baez

In chemical reaction network theory, ordinary differential equations are used to model the temporal change of chemical species concentration. As the functional form of these ordinary differential equations systems is derived from an…

Molecular Networks · Quantitative Biology 2025-02-27 Anna C. M. Thöni , William E. Robinson , Yoram Bachrach , Wilhelm T. S. Huck , Tal Kachman

The automated inference of physically interpretable (bio)chemical reaction network models from measured experimental data is a challenging problem whose solution has significant commercial and academic ramifications. It is demonstrated,…

Neural and Evolutionary Computing · Computer Science 2014-12-22 Dominic P. Searson , Mark J. Willis , Allen Wright
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