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A stochastic analysis of first-order reaction networks.

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TLDR
A stochastic model for a general system of first-order reactions in which each reaction may be either a conversion reaction or a catalytic reaction is derived and it is shown that the distribution of all the system components is a Poisson distribution at steady state.
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This article is published in Bulletin of Mathematical Biology.The article was published on 2005-09-01 and is currently open access. It has received 186 citations till now. The article focuses on the topics: Master equation & Stochastic process.

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Citations
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疟原虫var基因转换速率变化导致抗原变异[英]/Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

宁北芳, +1 more
TL;DR: PfPMP1)与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作�ly.

Chemical Engineering Scienceについて

正 城塚
TL;DR: In this article, the authors describe the first year of their first year in English language arts course, where they studied Calculus I, Chemistry I, and Expository Writing.
Journal ArticleDOI

Noise in biology

TL;DR: This short review covers the recent progress in understanding mechanisms and effects of fluctuations in biological systems of different scales and the basic approaches to their mathematical modeling.
Book ChapterDOI

Continuous Time Markov Chain Models for Chemical Reaction Networks

TL;DR: This chapter develops much of the mathematical machinery needed to describe the stochastic models of reaction networks and shows how to derive the deterministic law of mass action from the Markov chain model.
References
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疟原虫var基因转换速率变化导致抗原变异[英]/Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

宁北芳, +1 more
TL;DR: PfPMP1)与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作�ly.
Journal ArticleDOI

The Chemical Basis of Morphogenesis

TL;DR: In this article, it is suggested that a system of chemical substances, called morphogens, reacting together and diffusing through a tissue, is adequate to account for the main phenomena of morphogenesis.
Journal ArticleDOI

A General Method for Numerically Simulating the Stochastic Time Evolution of Coupled Chemical Reactions

TL;DR: In this paper, an exact method is presented for numerically calculating, within the framework of the stochastic formulation of chemical kinetics, the time evolution of any spatially homogeneous mixture of molecular species which interreact through a specified set of coupled chemical reaction channels.
Journal ArticleDOI

Stochastic Gene Expression in a Single Cell

TL;DR: This work constructed strains of Escherichia coli that enable detection of noise and discrimination between the two mechanisms by which it is generated and reveals how low intracellular copy numbers of molecules can fundamentally limit the precision of gene regulation.
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Frequently Asked Questions (10)
Q1. What are the contributions in "A stochastic analysis of first-order reaction networks" ?

The authors find the surprising, and apparently unknown, result that the time evolution of the second moments can be represented explicitly in terms of the eigenvalues and projections of the matrix that governs the evolution of the means. 

The mathematical formulation that leads to a direct solution of the moment equations for a well-stirred system can be extended to arbitrary networks of well-mixed compartments that are coupled by diffusion. The authors demonstrate that the eigenvalues that govern the evolution in such distributed systems are solutions of a one-parameter family of modified kinetic matrices and thus one can formally display the solution for the first two moments in this case as well. The authors anticipate that the analytical framework presented here will be extended to the stochastic analysis of nonlinear reaction networks, and their analysis of first-order reaction network will lead to insights into the local linear behavior of such networks. 

A major objective of many of the analyses treating biological systems is prediction of the stochastic variations or noise of the concentrations. 

Klein treated the number of balls in an urn as a measure of the occupancy of an energy state, and calculated the probability of the number of balls in an urn as a function of the transition probability and the initial distribution. 

If one considers each colony to be a distinct species, the open migration process is equivalent to an open conversion reaction system, and the proof for the stationary distribution of the number of individuals in each colony stated by Kelly (1979) may be considered as another proof for the distribution of the number of each species in an open conversion network that the authors derive later. 

The evolution of the surface morphology during epitaxial growth involves the nucleation and growth of atomic islands, and these processes may be described by first-order adsorption and desorption reactions coupled with diffusion along the surface. 

The mathematical formulation that leads to a direct solution of the moment equations for a well-stirred system can be extended to arbitrary networks of well-mixed compartments that are coupled by diffusion. 

For a closed system, one of the eigenvalues is zero and hence the longest characteristic time for the evolution of M and V will be identical. 

The function ν̂, which identifies a linear combination of species as a complex is onto, and the relation R has the properties (i) (C(i), C( j)) ∈ R if and only if there exists one and only one reaction of the form C(i)→ C( j), (ii) for every i there is a j = i such that (C(i), C( j)) ∈ R, (iii) (C(i), C(i)) ∈ R. 

It follows from (55) that the mean and variance for the mth species at the steady state are given byMm = Nπm = E[Nm ] σ 2(Nm ) = Nπm (1− πm) = E[Nm ] ( 1− E[Nm ]N) . (56)Notice that πm is the steady-state fraction of the mth molecular species in a deterministic description, and since this is fixed by the reaction rates, the variance σ 2(Nm ) does not approach the mean even as N → ∞.