Skip Navigation



Bioinformatics Advance Access published online on May 26, 2006
Bioinformatics, doi:10.1093/bioinformatics/btl271
This Article
Right arrow Advance Access manuscript (PDF) Freely available
Right arrow All Versions of this Article:
22/15/1895    most recent
btl271v1
Right arrow Comments: Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when Comments are posted
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Vidal Rodríguez, J.
Right arrow Articles by Blom, J. G.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Vidal Rodríguez, J.
Right arrow Articles by Blom, J. G.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author (2006). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
Received February 2, 2006
Revised May 2, 2006
Accepted May 22, 2006

Article

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

Jordi 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.
Jordi Vidal Rodríguez, E-mail: jrodrigu{at}science.uva.nl


  Abstract

Motivation: Many biochemical networks involve reactions localised 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 characterised 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.

Associate Editor: Alvis Brazma
Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 BioinformaticsHome page
M. Dobrzynski, J. V. Rodriguez, J. A. Kaandorp, and J. G. Blom
Computational methods for diffusion-influenced biochemical reactions
Bioinformatics, August 1, 2007; 23(15): 1969 - 1977.
[Abstract] [Full Text] [PDF]


Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.