Cargando…
The Abridgment and Relaxation Time for a Linear Multi-Scale Model Based on Multiple Site Phosphorylation
Random effect in cellular systems is an important topic in systems biology and often simulated with Gillespie’s stochastic simulation algorithm (SSA). Abridgment refers to model reduction that approximates a group of reactions by a smaller group with fewer species and reactions. This paper presents...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4532472/ https://www.ncbi.nlm.nih.gov/pubmed/26263559 http://dx.doi.org/10.1371/journal.pone.0133295 |
_version_ | 1782385225191391232 |
---|---|
author | Wang, Shuo Cao, Yang |
author_facet | Wang, Shuo Cao, Yang |
author_sort | Wang, Shuo |
collection | PubMed |
description | Random effect in cellular systems is an important topic in systems biology and often simulated with Gillespie’s stochastic simulation algorithm (SSA). Abridgment refers to model reduction that approximates a group of reactions by a smaller group with fewer species and reactions. This paper presents a theoretical analysis, based on comparison of the first exit time, for the abridgment on a linear chain reaction model motivated by systems with multiple phosphorylation sites. The analysis shows that if the relaxation time of the fast subsystem is much smaller than the mean firing time of the slow reactions, the abridgment can be applied with little error. This analysis is further verified with numerical experiments for models of bistable switch and oscillations in which linear chain system plays a critical role. |
format | Online Article Text |
id | pubmed-4532472 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-45324722015-08-20 The Abridgment and Relaxation Time for a Linear Multi-Scale Model Based on Multiple Site Phosphorylation Wang, Shuo Cao, Yang PLoS One Research Article Random effect in cellular systems is an important topic in systems biology and often simulated with Gillespie’s stochastic simulation algorithm (SSA). Abridgment refers to model reduction that approximates a group of reactions by a smaller group with fewer species and reactions. This paper presents a theoretical analysis, based on comparison of the first exit time, for the abridgment on a linear chain reaction model motivated by systems with multiple phosphorylation sites. The analysis shows that if the relaxation time of the fast subsystem is much smaller than the mean firing time of the slow reactions, the abridgment can be applied with little error. This analysis is further verified with numerical experiments for models of bistable switch and oscillations in which linear chain system plays a critical role. Public Library of Science 2015-08-11 /pmc/articles/PMC4532472/ /pubmed/26263559 http://dx.doi.org/10.1371/journal.pone.0133295 Text en © 2015 Wang, Cao http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Wang, Shuo Cao, Yang The Abridgment and Relaxation Time for a Linear Multi-Scale Model Based on Multiple Site Phosphorylation |
title | The Abridgment and Relaxation Time for a Linear Multi-Scale Model Based on Multiple Site Phosphorylation |
title_full | The Abridgment and Relaxation Time for a Linear Multi-Scale Model Based on Multiple Site Phosphorylation |
title_fullStr | The Abridgment and Relaxation Time for a Linear Multi-Scale Model Based on Multiple Site Phosphorylation |
title_full_unstemmed | The Abridgment and Relaxation Time for a Linear Multi-Scale Model Based on Multiple Site Phosphorylation |
title_short | The Abridgment and Relaxation Time for a Linear Multi-Scale Model Based on Multiple Site Phosphorylation |
title_sort | abridgment and relaxation time for a linear multi-scale model based on multiple site phosphorylation |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4532472/ https://www.ncbi.nlm.nih.gov/pubmed/26263559 http://dx.doi.org/10.1371/journal.pone.0133295 |
work_keys_str_mv | AT wangshuo theabridgmentandrelaxationtimeforalinearmultiscalemodelbasedonmultiplesitephosphorylation AT caoyang theabridgmentandrelaxationtimeforalinearmultiscalemodelbasedonmultiplesitephosphorylation AT wangshuo abridgmentandrelaxationtimeforalinearmultiscalemodelbasedonmultiplesitephosphorylation AT caoyang abridgmentandrelaxationtimeforalinearmultiscalemodelbasedonmultiplesitephosphorylation |