Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Bankhead, Armand, Mancini, Emiliano, Sims, Amy C., Baric, Ralph S., McWeeney, Shannon, Sloot, Peter M.A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Published by Elsevier B.V. 2011
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
_version_ 1783516902588416000
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
work_keys_str_mv AT bankheadarmand asimulationframeworktoinvestigateinvitroviralinfectiondynamics
AT manciniemiliano asimulationframeworktoinvestigateinvitroviralinfectiondynamics
AT simsamyc asimulationframeworktoinvestigateinvitroviralinfectiondynamics
AT baricralphs asimulationframeworktoinvestigateinvitroviralinfectiondynamics
AT mcweeneyshannon asimulationframeworktoinvestigateinvitroviralinfectiondynamics
AT slootpeterma asimulationframeworktoinvestigateinvitroviralinfectiondynamics
AT bankheadarmand simulationframeworktoinvestigateinvitroviralinfectiondynamics
AT manciniemiliano simulationframeworktoinvestigateinvitroviralinfectiondynamics
AT simsamyc simulationframeworktoinvestigateinvitroviralinfectiondynamics
AT baricralphs simulationframeworktoinvestigateinvitroviralinfectiondynamics
AT mcweeneyshannon simulationframeworktoinvestigateinvitroviralinfectiondynamics
AT slootpeterma simulationframeworktoinvestigateinvitroviralinfectiondynamics