Journal
BIOINFORMATICS
Volume 24, Issue 6, Pages 741-743Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btn041
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Funding
- Biotechnology and Biological Sciences Research Council Funding Source: Medline
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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, proteinprotein 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.
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