title: A Simulation Framework to Investigatein vitroViral Infection Dynamics.
abstract: Virus infection is a complex biological phenomenon for whichin vitroexperiments 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 ofin vitroviral 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.
authors.affiliation: Oregon Health and Science University, Portland, OR 97239-3098, USA.
authors.forename: Armand
authors.initials: A
authors.lastname: Bankhead
authors.forename: Emiliano
authors.initials: E
authors.lastname: Mancini
authors.forename: Amy C
authors.initials: AC
authors.lastname: Sims
authors.forename: Ralph S
authors.initials: RS
authors.lastname: Baric
authors.forename: Shannon
authors.initials: S
authors.lastname: McWeeney
authors.forename: Peter M A
authors.initials: PM
authors.lastname: Sloot
keywords: Cellular automata; SARS; infection dynamics; simulation