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Stochastic and Deterministic Models of Cellular p53 Regulation
The protein p53 is a key regulator of cellular response to a wide variety of stressors. In cancer cells inhibitory regulators of p53 such as MDM2 and MDMX proteins are often overexpressed. We apply in silico techniques to better understand the role and interactions of these proteins in a cell cycle...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3613726/ https://www.ncbi.nlm.nih.gov/pubmed/23565502 http://dx.doi.org/10.3389/fonc.2013.00064 |
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author | Leenders, Gerald B. Tuszynski, Jack A. |
author_facet | Leenders, Gerald B. Tuszynski, Jack A. |
author_sort | Leenders, Gerald B. |
collection | PubMed |
description | The protein p53 is a key regulator of cellular response to a wide variety of stressors. In cancer cells inhibitory regulators of p53 such as MDM2 and MDMX proteins are often overexpressed. We apply in silico techniques to better understand the role and interactions of these proteins in a cell cycle process. Furthermore we investigate the role of stochasticity in determining system behavior. We have found that stochasticity is able to affect system behavior profoundly. We also derive a general result for the way in which initially synchronized oscillating stochastic systems will fall out of synchronization with each other. |
format | Online Article Text |
id | pubmed-3613726 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-36137262013-04-05 Stochastic and Deterministic Models of Cellular p53 Regulation Leenders, Gerald B. Tuszynski, Jack A. Front Oncol Oncology The protein p53 is a key regulator of cellular response to a wide variety of stressors. In cancer cells inhibitory regulators of p53 such as MDM2 and MDMX proteins are often overexpressed. We apply in silico techniques to better understand the role and interactions of these proteins in a cell cycle process. Furthermore we investigate the role of stochasticity in determining system behavior. We have found that stochasticity is able to affect system behavior profoundly. We also derive a general result for the way in which initially synchronized oscillating stochastic systems will fall out of synchronization with each other. Frontiers Media S.A. 2013-04-02 /pmc/articles/PMC3613726/ /pubmed/23565502 http://dx.doi.org/10.3389/fonc.2013.00064 Text en Copyright © 2013 Leenders and Tuszynski. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc. |
spellingShingle | Oncology Leenders, Gerald B. Tuszynski, Jack A. Stochastic and Deterministic Models of Cellular p53 Regulation |
title | Stochastic and Deterministic Models of Cellular p53 Regulation |
title_full | Stochastic and Deterministic Models of Cellular p53 Regulation |
title_fullStr | Stochastic and Deterministic Models of Cellular p53 Regulation |
title_full_unstemmed | Stochastic and Deterministic Models of Cellular p53 Regulation |
title_short | Stochastic and Deterministic Models of Cellular p53 Regulation |
title_sort | stochastic and deterministic models of cellular p53 regulation |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3613726/ https://www.ncbi.nlm.nih.gov/pubmed/23565502 http://dx.doi.org/10.3389/fonc.2013.00064 |
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