Skip Navigation



Bioinformatics Advance Access published online on November 22, 2007
Bioinformatics, doi:10.1093/bioinformatics/btm560
This Article
Right arrow Advance Access manuscript (PDF) Freely available
Right arrow Supplementary Data
Right arrow All Versions of this Article:
24/2/209    most recent
btm560v1
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 Hardy, S.
Right arrow Articles by Robillard, P. N.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Hardy, S.
Right arrow Articles by Robillard, P. N.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author (2007). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Petri net-based method for the analysis of the dynamics of signal propagation in signaling pathways

Simon Hardy 1,* and Pierre N. Robillard 1

1Department of Computer Engineering, École Polytechnique de Montréal, P.O. Box 6079, Station Centre-Ville, Montréal, H3C 3A7, Canada

*To whom correspondence should be addressed. Mr. Simon Hardy, E-mail: simon.hardy{at}polymtl.ca


  Abstract

Motivation: Cellular signaling networks are dynamic systems which propagate and process information, and, ultimately, cause phenotypical responses. Understanding the circuitry of the information flow in cells is one of the keys to understanding complex cellular processes. The development of computational quantitative models is a promising avenue for attaining this goal. Not only does the analysis of the simulation data based on the concentration variations of biological compounds yields information about systemic state changes, but it is also very helpful for obtaining information about the dynamics of signal propagation.

Results: This paper introduces a new method for analyzing the dynamics of signal propagation in signaling pathways using Petri net theory. The method is demonstrated with the Ca2+/calmodulin-dependent protein kinase II (CaMKII) regulation network. The results constitute temporal information about signal propagation in the network, a simplified graphical representation of the network and of the signal propagation dynamics and a characterization of some signaling routes as regulation motifs.

Contact: simon.hardy{at}polymtl.ca

Associate Editor: Prof. Martin Bishop

Received on July 8, 2007; revised on October 9, 2007; accepted on November 5, 2007

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
 J. Biol. Chem.Home page
A. Ma'ayan
Insights into the Organization of Biochemical Regulatory Networks Using Graph Theory Analyses
J. Biol. Chem., February 27, 2009; 284(9): 5451 - 5455.
[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.