- A simulation framework to investigate in vitro viral infection dynamics
- Journal of Computational Science
- Volume | Issue number
- 4 | 3
- Number of pages
- Document type
- Faculty of Science (FNWI)
- Informatics Institute (IVI)
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 h post infection. Using a simulated annealing algorithm we tune free parameters with data from SARSCoV 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.
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