About: A Simulation Framework to Investigate in vitro Viral Infection Dynamics

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	A Simulation Framework to Investigate in vitro Viral Infection Dynamics
Creator	Baric, Ralph Sims, Amy Bankhead, Armand Mancini, Emiliano Bankhead, A Mancini, E Mcweeney, Shannon Sims, A Sloot, Peter Sloot, S
Source	Elsevier; Medline; PMC
abstract	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. Using a simulated annealing algorithm we tune free parameters with data from SARS-CoV infection of cultured lung epithelial cells. We also 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.
has issue date	2013-05-01(xsd:dateTime)
bibo:doi	10.1016/j.jocs.2011.08.007
bibo:pmid	23682300
has license	green-oa
sha1sum (hex)	037084a9d4ae6eb98e6fde025190980053981a70
schema:url	https://doi.org/10.1016/j.jocs.2011.08.007
resource representing a document's title	A Simulation Framework to Investigate in vitro Viral Infection Dynamics
has PubMed Central identifier	PMC3652481
has PubMed identifier	23682300
schema:publication	Journal of Computational Science
resource representing a document's body	covid:037084a9d4ae6eb98e6fde025190980053981a70#body_text
is schema:about of	named entity 'simulation framework' named entity 'CC BY-NC-ND' named entity 'PUBLISHED' named entity 'ACADEMIC' named entity 'DYNAMICS' named entity 'VERSION' named entity 'P.M.' named entity 'BANKHEAD' named entity 'TO INVESTIGATE' named entity 'SIMULATION' named entity 'HTTPS' named entity 'DARE' named entity 'VIRAL INFECTION' named entity 'CREATIVE COMMONS' named entity 'LICENSE' named entity 'VIRAL INFECTION' named entity 'IN VITRO' named entity 'UVA' named entity 'ORG' named entity 'NC-' named entity 'CITATION' named entity 'TO INVESTIGATE' named entity 'DYNAMICS' named entity 'LINK' named entity 'IN VITRO' named entity 'SIMS' named entity 'PUBLICATION' named entity 'SIMULATION' named entity 'REPOSITORY' named entity 'LICENSES' named entity 'viral infection' named entity 'Simulation Framework' named entity 'viral particles' named entity 'infection' named entity 'virions' named entity 'virus' named entity 'host cells' named entity 'research projects' named entity 'viral infection' named entity 'Poisson' named entity 'epithelial' named entity 'binomial distribution' named entity 'titer' named entity 'MOI' named entity 'computational model' named entity 'green fluorescent protein' named entity 'cell culture' named entity 'titer' named entity 'host cell' named entity 'virus' named entity 'infection' named entity 'virus' named entity 'titer' named entity 'probability' named entity 'LHS' named entity 'immune response' named entity 'titer' named entity 'titer' named entity 'GFP' named entity 'host cells' named entity 'epithelial cells' named entity 'lungs' named entity 'PFU' named entity 'sampling method' named entity 'antimycotic' named entity 'infection' named entity 'virus' named entity 'infectivity' named entity 'lattice point' named entity 'SARS-CoV' named entity 'virus' named entity 'multiplicity of infection'

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