Biological pathway kinetic rate constants are scale-invariant

by: Scott Grandison, Richard J Morris

Bioinformatics, Vol. 24, No. 6. (15 March 2008), pp. 741-743.

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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@bbsrc.ac.uk 10.1093/bioinformatics/btn041

@article{citeulike:2753217, 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@bbsrc.ac.uk 10.1093/bioinformatics/btn041}, author = {Grandison, Scott and Morris, Richard J. }, citeulike-article-id = {2753217}, doi = {10.1093/bioinformatics/btn041}, journal = {Bioinformatics}, keywords = {simulation}, month = {March}, number = {6}, pages = {741--743}, posted-at = {2008-05-04 12:21:07}, priority = {2}, title = {Biological pathway kinetic rate constants are scale-invariant}, url = {http://dx.doi.org/10.1093/bioinformatics/btn041}, volume = {24}, year = {2008} }

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TY - JOUR ID - citeulike:2753217 L3 - citeulike-article-id:2753217 TI - Biological pathway kinetic rate constants are scale-invariant JF - Bioinformatics VL - 24 IS - 6 SP - 741 EP - 743 N2 - 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@bbsrc.ac.uk 10.1093/bioinformatics/btn041 KW - simulation AU - Grandison, Scott AU - Morris, Richard PY - 2008/03/15/ UR - http://dx.doi.org/10.1093/bioinformatics/btn041 ER -

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