A simulation framework to investigate in vitro viral infection dynamics

Armand Bankhead, Emiliano Mancini, Amy C. Sims, Ralph S. Baric, Shannon Mcweeney, Peter M.A. Sloot

Research output: Contribution to journalConference articlepeer-review

3 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)1798-1807
Number of pages10
JournalProcedia Computer Science
StatePublished - 2011
Event11th International Conference on Computational Science, ICCS 2011 - Singapore, Singapore
Duration: Jun 1 2011Jun 3 2011


  • Cellular automata
  • Infection dynamics
  • SARS
  • Simulation

ASJC Scopus subject areas

  • Computer Science(all)


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