Skip Navigation


Bioinformatics Advance Access originally published online on January 30, 2008
Bioinformatics 2008 24(6):741-743; doi:10.1093/bioinformatics/btn041
This Article
Right arrow Full Text
Right arrow Full Text (Print PDF)
Right arrow All Versions of this Article:
24/6/741    most recent
btn041v1
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 arrowRequest Permissions
Google Scholar
Right arrow Articles by Grandison, S.
Right arrow Articles by Morris, R. J.
PubMed
Right arrow PubMed Citation
Right arrow Articles by Grandison, S.
Right arrow Articles by Morris, R. J.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author 2008. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Biological pathway kinetic rate constants are scale-invariant

Scott Grandison and Richard J. Morris *

Department of Computational & Systems Biology, John Innes Centre, Norwich Research Park, Colney Lane, NR4 7UH Norwich, UK

*To whom correspondence should be addressed.


  Abstract

Motivation: Scale-free networks have had a profound impact in Biology. Network theory is now used routinely to visualize, navigate through, and help understand gene networks, protein–protein interactions, regulatory networks and metabolic pathways. Here we analyse the numerical rather than topological properties of biological networks and focus on the study of kinetic rate constants within pathways.

Results: We have analysed all current entries in the BioModels database and show that the kinetic rate parameters follow Benford's; law closely. The cumulative histogram plot reveals an underlying power-law. This implies that these data are scale-invariant, thus placing biological network topology and their chemistry on an equivalent ‘scale-free’ power-law foundation.

Contact: Richard.Morris{at}bbsrc.ac.uk

Associate Editor: Martin Bishop

Received on October 3, 2007; revised on January 24, 2008; accepted on January 25, 2008

Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?




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.