Skip Navigation


Bioinformatics Advance Access originally published online on September 9, 2004
Bioinformatics 2005 21(3):357-363; doi:10.1093/bioinformatics/bti018
This Article
Right arrow Full Text Freely available
Right arrow FREE Full Text (Print PDF) Freely available
Right arrow All Versions of this Article:
21/3/357    most recent
bti018v1
Right arrow Alert me when this article is cited
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 ISI Web of Science
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 arrow Search for citing articles in:
ISI Web of Science (10)
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Pettinen, A.
Right arrow Articles by Linne, M.-L.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Pettinen, A.
Right arrow Articles by Linne, M.-L.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

Bioinformatics vol. 21 issue 3 © Oxford University Press 2005; all rights reserved.

Simulation tools for biochemical networks: evaluation of performance and usability

Antti Pettinen *, Tommi Aho , Olli-Pekka Smolander , Tiina Manninen , Antti Saarinen , Kaisa-Leena Taattola , Olli Yli-Harja and Marja-Leena Linne

Institute of Signal Processing, Tampere University of Technology P.O. Box 553, 33101 Tampere, Finland

*To whom correspondence should be addressed.

Motivation: Simulation of dynamic biochemical systems is receiving considerable attention due to increasing availability of experimental data of complex cellular functions. Numerous simulation tools have been developed for numerical simulation of the behavior of a system described in mathematical form. However, there exist only a few evaluation studies of these tools. Knowledge of the properties and capabilities of the simulation tools would help bioscientists in building models based on experimental data.

Results: We examine selected simulation tools that are intended for the simulation of biochemical systems. We choose four of them for more detailed study and perform time series simulations using a specific pathway describing the concentration of the active form of protein kinase C. We conclude that the simulation results are convergent between the chosen simulation tools. However, the tools differ in their usability, support for data transfer to other programs and support for automatic parameter estimation. From the experimentalists’ point of view, all these are properties that need to be emphasized in the future.

Contact: antti.pettinen{at}tut.fi


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
 Brief BioinformHome page
D. Gilbert, H. Fuss, X. Gu, R. Orton, S. Robinson, V. Vyshemirsky, M. J. Kurth, C. S. Downes, and W. Dubitzky
Computational methodologies for modelling, analysis and simulation of signalling networks
Brief Bioinform, December 1, 2006; 7(4): 339 - 353.
[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.