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Stochastic Gene Expression Revisited

We investigate the model of gene expression in the form of Iterated Function System (IFS), where the probability of choice of any iterated map depends on the state of the phase space. Random jump times of the process mark activation periods of the gene when pre-mRNA molecules are produced before mRN...

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Detalles Bibliográficos
Autores principales: Tomski, Andrzej, Zakarczemny, Maciej
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8145461/
https://www.ncbi.nlm.nih.gov/pubmed/33926131
http://dx.doi.org/10.3390/genes12050648
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author Tomski, Andrzej
Zakarczemny, Maciej
author_facet Tomski, Andrzej
Zakarczemny, Maciej
author_sort Tomski, Andrzej
collection PubMed
description We investigate the model of gene expression in the form of Iterated Function System (IFS), where the probability of choice of any iterated map depends on the state of the phase space. Random jump times of the process mark activation periods of the gene when pre-mRNA molecules are produced before mRNA and protein processing phases occur. The main idea is inspired by the continuous-time piecewise deterministic Markov process describing stochastic gene expression. We show that for our system there exists a unique invariant limit measure. We provide full probabilistic description of the process with a comparison of our results to those obtained for the model with continuous time.
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spelling pubmed-81454612021-05-26 Stochastic Gene Expression Revisited Tomski, Andrzej Zakarczemny, Maciej Genes (Basel) Article We investigate the model of gene expression in the form of Iterated Function System (IFS), where the probability of choice of any iterated map depends on the state of the phase space. Random jump times of the process mark activation periods of the gene when pre-mRNA molecules are produced before mRNA and protein processing phases occur. The main idea is inspired by the continuous-time piecewise deterministic Markov process describing stochastic gene expression. We show that for our system there exists a unique invariant limit measure. We provide full probabilistic description of the process with a comparison of our results to those obtained for the model with continuous time. MDPI 2021-04-26 /pmc/articles/PMC8145461/ /pubmed/33926131 http://dx.doi.org/10.3390/genes12050648 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Tomski, Andrzej
Zakarczemny, Maciej
Stochastic Gene Expression Revisited
title Stochastic Gene Expression Revisited
title_full Stochastic Gene Expression Revisited
title_fullStr Stochastic Gene Expression Revisited
title_full_unstemmed Stochastic Gene Expression Revisited
title_short Stochastic Gene Expression Revisited
title_sort stochastic gene expression revisited
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8145461/
https://www.ncbi.nlm.nih.gov/pubmed/33926131
http://dx.doi.org/10.3390/genes12050648
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