Bioinformatics Advance Access published online on March 6, 2007
Bioinformatics, doi:10.1093/bioinformatics/btm044
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Simulating Epstein-Barr Virus Infection with C-ImmSim
1Istituto Applicazioni del Calcolo (IAC) "M. Picone"-CNR, Viale del Policlinico, 137, 00161 Rome, Italy. 2Virginia Bioinformatics Institute, Washington St., MC 0477, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA. 3Department of Pathology Jaharis Building, Tufts University School of Medicine, 150 Harrison Ave., Boston MA 02111, USA.
*To whom correspondence should be addressed. Prof. David Thorley-Lawson, E-mail: david.thorley-lawson{at}tufts.edu
| Abstract |
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Motivation: Epstein-Barr virus (EBV) infects greater than 90% of humans benignly for life but can be associated with tumors. It is a uniquely human pathogen that is amenable to quantitative analysis; however there is no applicable animal model. Computer models may provide a virtual environment to perform experiments not possible in human volunteers.
Results: We report the application of a relatively simple stochastic cellular automaton (C-ImmSim) to the modeling of EBV infection. Infected B-cell dynamics in the acute and chronic phases of infection correspond well to clinical data including the establishment of a long term persistent infection (up to 10 years) that is absolutely dependent on access of latently infected B cells to the peripheral pool where they are not subject to immunosurveillance. In the absence of this compartment the infection is cleared.
Availability: The latest version 6 of C-ImmSim is available under the GNU General Public License and is downloadable from www.iac.cnr.it/~filippo/cimmsim.html
Associate Editor: Dr. Jonathan Wren
#Current address: Dept. of Biochemistry and Biotechnology, KNUST, Kumasi, Ghana
Received on October 27, 2006; revised on January 15, 2007; accepted on February 3, 2007
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