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Bioinformatics Advance Access originally published online on May 26, 2006
Bioinformatics 2006 22(15):1895-1901; doi:10.1093/bioinformatics/btl271
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© The Author 2006. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Spatial stochastic modelling of the phosphoenolpyruvate-dependent phosphotransferase (PTS) pathway in Escherichia coli

J. Vidal Rodríguez 1,*, Jaap A. Kaandorp 1, Maciej Dobrzynski 2 and Joke G. Blom 2

1 Section Computational Science, Faculty of Science, University of Amsterdam Kruislaan 403, 1098 SJ Amsterdam, The Netherlands
2 Center for Mathematics and Computer Science (CWI) Kruislaan 413, 1098 SJ Amsterdam, The Netherlands

*To whom correspondence should be addressed.

Motivation: Many biochemical networks involve reactions localized on the cell membrane. This can give rise to spatial gradients of the concentration of cytosolic species. Moreover, the number of membrane molecules can be small and stochastic effects can become relevant. Pathways usually consist of a complex interaction network and are characterized by a large set of parameters. The inclusion of spatial and stochastic effects is a major challenge in developing quantitative and dynamic models of pathways.

Results: We have developed a particle-based spatial stochastic method (GMP) to simulate biochemical networks in space, including fluctuations from the diffusion of particles and reactions. Gradients emerging from membrane reactions can be resolved. As case studies for the GMP method we used a simple gene expression system and the phosphoenolpyruvate:glucose phosphotransferase system pathway.

Availability: The source code for the GMP method is available at http://www.science.uva.nl/research/scs/CellMath/GMP

Contact: jrodrigu{at}science.uva.nl

Received on February 2, 2006; revised on May 2, 2006; accepted on May 22, 2006

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M. Dobrzynski, J. V. Rodriguez, J. A. Kaandorp, and J. G. Blom
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