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Delay chemical master equation: direct and closed-form solutions

The stochastic simulation algorithm (SSA) describes the time evolution of a discrete nonlinear Markov process. This stochastic process has a probability density function that is the solution of a differential equation, commonly known as the chemical master equation (CME) or forward-Kolmogorov equati...

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Detalles Bibliográficos
Autores principales: Leier, Andre, Marquez-Lago, Tatiana T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society Publishing 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4528653/
https://www.ncbi.nlm.nih.gov/pubmed/26345616
http://dx.doi.org/10.1098/rspa.2015.0049
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author Leier, Andre
Marquez-Lago, Tatiana T.
author_facet Leier, Andre
Marquez-Lago, Tatiana T.
author_sort Leier, Andre
collection PubMed
description The stochastic simulation algorithm (SSA) describes the time evolution of a discrete nonlinear Markov process. This stochastic process has a probability density function that is the solution of a differential equation, commonly known as the chemical master equation (CME) or forward-Kolmogorov equation. In the same way that the CME gives rise to the SSA, and trajectories of the latter are exact with respect to the former, trajectories obtained from a delay SSA are exact representations of the underlying delay CME (DCME). However, in contrast to the CME, no closed-form solutions have so far been derived for any kind of DCME. In this paper, we describe for the first time direct and closed solutions of the DCME for simple reaction schemes, such as a single-delayed unimolecular reaction as well as chemical reactions for transcription and translation with delayed mRNA maturation. We also discuss the conditions that have to be met such that such solutions can be derived.
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spelling pubmed-45286532015-09-04 Delay chemical master equation: direct and closed-form solutions Leier, Andre Marquez-Lago, Tatiana T. Proc Math Phys Eng Sci Research Articles The stochastic simulation algorithm (SSA) describes the time evolution of a discrete nonlinear Markov process. This stochastic process has a probability density function that is the solution of a differential equation, commonly known as the chemical master equation (CME) or forward-Kolmogorov equation. In the same way that the CME gives rise to the SSA, and trajectories of the latter are exact with respect to the former, trajectories obtained from a delay SSA are exact representations of the underlying delay CME (DCME). However, in contrast to the CME, no closed-form solutions have so far been derived for any kind of DCME. In this paper, we describe for the first time direct and closed solutions of the DCME for simple reaction schemes, such as a single-delayed unimolecular reaction as well as chemical reactions for transcription and translation with delayed mRNA maturation. We also discuss the conditions that have to be met such that such solutions can be derived. The Royal Society Publishing 2015-07-08 /pmc/articles/PMC4528653/ /pubmed/26345616 http://dx.doi.org/10.1098/rspa.2015.0049 Text en http://creativecommons.org/licenses/by/4.0/ © 2015 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.
spellingShingle Research Articles
Leier, Andre
Marquez-Lago, Tatiana T.
Delay chemical master equation: direct and closed-form solutions
title Delay chemical master equation: direct and closed-form solutions
title_full Delay chemical master equation: direct and closed-form solutions
title_fullStr Delay chemical master equation: direct and closed-form solutions
title_full_unstemmed Delay chemical master equation: direct and closed-form solutions
title_short Delay chemical master equation: direct and closed-form solutions
title_sort delay chemical master equation: direct and closed-form solutions
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4528653/
https://www.ncbi.nlm.nih.gov/pubmed/26345616
http://dx.doi.org/10.1098/rspa.2015.0049
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