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Infectio: a Generic Framework for Computational Simulation of Virus Transmission between Cells

Yakimovich, Artur; Yakimovich, Yauhen; Schmid, Michael; Sbalzarini, Ivo F.; Greber, Urs F.; (2016) Infectio: a Generic Framework for Computational Simulation of Virus Transmission between Cells. mSphere , 1 (1) , Article e00078-15. 10.1128/mSphere.00078-15. Green open access

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Abstract

Viruses spread between cells, tissues, and organisms by cell-free and cell-cell mechanisms, depending on the cell type, the nature of the virus, or the phase of the infection cycle. The mode of viral transmission has a large impact on disease development, the outcome of antiviral therapies or the efficacy of gene therapy protocols. The transmission mode of viruses can be addressed in tissue culture systems using live-cell imaging. Yet even in relatively simple cell cultures, the mechanisms of viral transmission are difficult to distinguish. Here we present a crossplatform software framework called “Infectio,” which is capable of simulating transmission phenotypes in tissue culture of virtually any virus. Infectio can estimate interdependent biological parameters, for example for vaccinia virus infection, and differentiate between cell-cell and cell-free virus spreading. Infectio assists in elucidating virus transmission mechanisms, a feature useful for designing strategies of perturbing or enhancing viral transmission. The complexity of the Infectio software is low compared to that of other software commonly used to quantitate features of cell biological images, which yields stable and relatively error-free output from Infectio. The software is open source (GPLv3 license), and operates on the major platforms (Windows, Mac, and Linux). The complete source code can be downloaded from http://infectio.github.io/index.html.

Type: Article
Title: Infectio: a Generic Framework for Computational Simulation of Virus Transmission between Cells
Open access status: An open access version is available from UCL Discovery
DOI: 10.1128/mSphere.00078-15
Publisher version: http://dx.doi.org/10.1128/mSphere.00078-15
Language: English
Additional information: © 2016 Yakimovich et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.
Keywords: infection spread, numerical simulation, hybrid modeling, multiscale modeling, cellular automata, particle strength exchange, diffusion, convection, advection, fluorescence microscopy, cell population, phenotypic properties
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Lab for Molecular Cell Bio MRC-UCL
URI: https://discovery.ucl.ac.uk/id/eprint/1476014
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