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Mathematical Models of Death Signaling Networks
This review provides an overview of the progress made by computational and systems biologists in characterizing different cell death regulatory mechanisms that constitute the cell death network. We define the cell death network as a comprehensive decision-making mechanism that controls multiple deat...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9602293/ https://www.ncbi.nlm.nih.gov/pubmed/37420422 http://dx.doi.org/10.3390/e24101402 |
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author | Srinivasan, Madhumita Clarke, Robert Kraikivski, Pavel |
author_facet | Srinivasan, Madhumita Clarke, Robert Kraikivski, Pavel |
author_sort | Srinivasan, Madhumita |
collection | PubMed |
description | This review provides an overview of the progress made by computational and systems biologists in characterizing different cell death regulatory mechanisms that constitute the cell death network. We define the cell death network as a comprehensive decision-making mechanism that controls multiple death execution molecular circuits. This network involves multiple feedback and feed-forward loops and crosstalk among different cell death-regulating pathways. While substantial progress has been made in characterizing individual cell death execution pathways, the cell death decision network is poorly defined and understood. Certainly, understanding the dynamic behavior of such complex regulatory mechanisms can be only achieved by applying mathematical modeling and system-oriented approaches. Here, we provide an overview of mathematical models that have been developed to characterize different cell death mechanisms and intend to identify future research directions in this field. |
format | Online Article Text |
id | pubmed-9602293 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-96022932022-10-27 Mathematical Models of Death Signaling Networks Srinivasan, Madhumita Clarke, Robert Kraikivski, Pavel Entropy (Basel) Review This review provides an overview of the progress made by computational and systems biologists in characterizing different cell death regulatory mechanisms that constitute the cell death network. We define the cell death network as a comprehensive decision-making mechanism that controls multiple death execution molecular circuits. This network involves multiple feedback and feed-forward loops and crosstalk among different cell death-regulating pathways. While substantial progress has been made in characterizing individual cell death execution pathways, the cell death decision network is poorly defined and understood. Certainly, understanding the dynamic behavior of such complex regulatory mechanisms can be only achieved by applying mathematical modeling and system-oriented approaches. Here, we provide an overview of mathematical models that have been developed to characterize different cell death mechanisms and intend to identify future research directions in this field. MDPI 2022-10-01 /pmc/articles/PMC9602293/ /pubmed/37420422 http://dx.doi.org/10.3390/e24101402 Text en © 2022 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 | Review Srinivasan, Madhumita Clarke, Robert Kraikivski, Pavel Mathematical Models of Death Signaling Networks |
title | Mathematical Models of Death Signaling Networks |
title_full | Mathematical Models of Death Signaling Networks |
title_fullStr | Mathematical Models of Death Signaling Networks |
title_full_unstemmed | Mathematical Models of Death Signaling Networks |
title_short | Mathematical Models of Death Signaling Networks |
title_sort | mathematical models of death signaling networks |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9602293/ https://www.ncbi.nlm.nih.gov/pubmed/37420422 http://dx.doi.org/10.3390/e24101402 |
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