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A Simulation Framework to Investigate in vitro Viral Infection Dynamics
Virus infection is a complex biological phenomenon for which in vitro experiments provide a uniquely concise view where data is often obtained from a single population of cells, under controlled environmental conditions. Nonetheless, data interpretation and real understanding of viral dynamics is st...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Published by Elsevier B.V.
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7129957/ https://www.ncbi.nlm.nih.gov/pubmed/32288900 http://dx.doi.org/10.1016/j.procs.2011.04.195 |
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author | Bankhead, Armand Mancini, Emiliano Sims, Amy C. Baric, Ralph S. McWeeney, Shannon Sloot, Peter M.A. |
author_facet | Bankhead, Armand Mancini, Emiliano Sims, Amy C. Baric, Ralph S. McWeeney, Shannon Sloot, Peter M.A. |
author_sort | Bankhead, Armand |
collection | PubMed |
description | Virus infection is a complex biological phenomenon for which in vitro experiments provide a uniquely concise view where data is often obtained from a single population of cells, under controlled environmental conditions. Nonetheless, data interpretation and real understanding of viral dynamics is still hampered by the sheer complexity of the various intertwined spatio-temporal processes. In this paper we present a tool to address these issues: a cellular automata model describing critical aspects of in vitro viral infections taking into account spatial characteristics of virus spreading within a culture well. The aim of the model is to understand the key mechanisms of SARS-CoV infection dynamics during the first 24 hours post infection. We interrogate the model using a Latin Hypercube sensitivity analysis to identify which mechanisms are critical to the observed infection of host cells and the release of measured virus particles. |
format | Online Article Text |
id | pubmed-7129957 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Published by Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-71299572020-04-08 A Simulation Framework to Investigate in vitro Viral Infection Dynamics Bankhead, Armand Mancini, Emiliano Sims, Amy C. Baric, Ralph S. McWeeney, Shannon Sloot, Peter M.A. Procedia Comput Sci Article Virus infection is a complex biological phenomenon for which in vitro experiments provide a uniquely concise view where data is often obtained from a single population of cells, under controlled environmental conditions. Nonetheless, data interpretation and real understanding of viral dynamics is still hampered by the sheer complexity of the various intertwined spatio-temporal processes. In this paper we present a tool to address these issues: a cellular automata model describing critical aspects of in vitro viral infections taking into account spatial characteristics of virus spreading within a culture well. The aim of the model is to understand the key mechanisms of SARS-CoV infection dynamics during the first 24 hours post infection. We interrogate the model using a Latin Hypercube sensitivity analysis to identify which mechanisms are critical to the observed infection of host cells and the release of measured virus particles. Published by Elsevier B.V. 2011 2011-05-14 /pmc/articles/PMC7129957/ /pubmed/32288900 http://dx.doi.org/10.1016/j.procs.2011.04.195 Text en Copyright © 2011 Published by Elsevier B.V. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Bankhead, Armand Mancini, Emiliano Sims, Amy C. Baric, Ralph S. McWeeney, Shannon Sloot, Peter M.A. A Simulation Framework to Investigate in vitro Viral Infection Dynamics |
title | A Simulation Framework to Investigate in vitro Viral Infection Dynamics |
title_full | A Simulation Framework to Investigate in vitro Viral Infection Dynamics |
title_fullStr | A Simulation Framework to Investigate in vitro Viral Infection Dynamics |
title_full_unstemmed | A Simulation Framework to Investigate in vitro Viral Infection Dynamics |
title_short | A Simulation Framework to Investigate in vitro Viral Infection Dynamics |
title_sort | simulation framework to investigate in vitro viral infection dynamics |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7129957/ https://www.ncbi.nlm.nih.gov/pubmed/32288900 http://dx.doi.org/10.1016/j.procs.2011.04.195 |
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