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System size reduction in stochastic simulations of the facilitated diffusion mechanism

BACKGROUND: Site-specific Transcription Factors (TFs) are proteins that bind to specific sites on the DNA and control the activity of a target gene by enhancing or decreasing the rate at which the gene is transcribed by RNA polymerase. The process by which TF molecules locate their target sites is a...

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Autor principal: Zabet, Nicolae Radu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3567987/
https://www.ncbi.nlm.nih.gov/pubmed/22958362
http://dx.doi.org/10.1186/1752-0509-6-121
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author Zabet, Nicolae Radu
author_facet Zabet, Nicolae Radu
author_sort Zabet, Nicolae Radu
collection PubMed
description BACKGROUND: Site-specific Transcription Factors (TFs) are proteins that bind to specific sites on the DNA and control the activity of a target gene by enhancing or decreasing the rate at which the gene is transcribed by RNA polymerase. The process by which TF molecules locate their target sites is a key component of transcriptional regulation. Therefore it is essential to gain insight into the mechanisms by which TFs search for the target sites. Research in this area uses experimental and analytical approaches, but also stochastic simulations of the search process. Previous work based on stochastic simulations focussed only on short sequences, primarily for reasons of technical feasibility. Many of these studies had to disregard possible biases introduced by reducing a genome-wide system to a smaller subsystem. In particular, we identified crucial parameters that require adjustment, which were not adequately changed in these previous studies. RESULTS: We investigated several methods that adequately adapt the parameters of stochastic simulations of the facilitated diffusion, when the full sequence space is reduced to smaller regions of interest. We found two methods that scale the system accordingly: the copy number model and the association rate model. We systematically compared the results produced by simulations of the subsystem with respect to the original system. Our results confirmed that the copy number model is adequate only for high abundance TFs, while for low abundance TFs the association rate model is the only one that reproduces with high accuracy the results of the full system. CONCLUSIONS: We propose a strategy to reduce the size of the system that adequately adapts important parameters to capture the behaviour of the full system. This enables correct simulations of a smaller sequence space (which can be as small as 100 Kbp) and, thus, provides independence from computationally intensive genome-wide simulations of the facilitated diffusion mechanism.
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spelling pubmed-35679872013-02-13 System size reduction in stochastic simulations of the facilitated diffusion mechanism Zabet, Nicolae Radu BMC Syst Biol Research Article BACKGROUND: Site-specific Transcription Factors (TFs) are proteins that bind to specific sites on the DNA and control the activity of a target gene by enhancing or decreasing the rate at which the gene is transcribed by RNA polymerase. The process by which TF molecules locate their target sites is a key component of transcriptional regulation. Therefore it is essential to gain insight into the mechanisms by which TFs search for the target sites. Research in this area uses experimental and analytical approaches, but also stochastic simulations of the search process. Previous work based on stochastic simulations focussed only on short sequences, primarily for reasons of technical feasibility. Many of these studies had to disregard possible biases introduced by reducing a genome-wide system to a smaller subsystem. In particular, we identified crucial parameters that require adjustment, which were not adequately changed in these previous studies. RESULTS: We investigated several methods that adequately adapt the parameters of stochastic simulations of the facilitated diffusion, when the full sequence space is reduced to smaller regions of interest. We found two methods that scale the system accordingly: the copy number model and the association rate model. We systematically compared the results produced by simulations of the subsystem with respect to the original system. Our results confirmed that the copy number model is adequate only for high abundance TFs, while for low abundance TFs the association rate model is the only one that reproduces with high accuracy the results of the full system. CONCLUSIONS: We propose a strategy to reduce the size of the system that adequately adapts important parameters to capture the behaviour of the full system. This enables correct simulations of a smaller sequence space (which can be as small as 100 Kbp) and, thus, provides independence from computationally intensive genome-wide simulations of the facilitated diffusion mechanism. BioMed Central 2012-09-08 /pmc/articles/PMC3567987/ /pubmed/22958362 http://dx.doi.org/10.1186/1752-0509-6-121 Text en Copyright ©2012 Zabet; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Zabet, Nicolae Radu
System size reduction in stochastic simulations of the facilitated diffusion mechanism
title System size reduction in stochastic simulations of the facilitated diffusion mechanism
title_full System size reduction in stochastic simulations of the facilitated diffusion mechanism
title_fullStr System size reduction in stochastic simulations of the facilitated diffusion mechanism
title_full_unstemmed System size reduction in stochastic simulations of the facilitated diffusion mechanism
title_short System size reduction in stochastic simulations of the facilitated diffusion mechanism
title_sort system size reduction in stochastic simulations of the facilitated diffusion mechanism
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3567987/
https://www.ncbi.nlm.nih.gov/pubmed/22958362
http://dx.doi.org/10.1186/1752-0509-6-121
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