Failed "nonaccelerating" models of prokaryote gene regulatory networks

Gagen, M. J. and Mattick, J. S. (2004) Failed "nonaccelerating" models of prokaryote gene regulatory networks. Quantitative Biology, 1-13.


Author Gagen, M. J.
Mattick, J. S.
Title Failed "nonaccelerating" models of prokaryote gene regulatory networks
Journal name Quantitative Biology
Publication date 2004-01-04
Sub-type Article (original research)
Start page 1
End page 13
Total pages 13
Place of publication United States
Publisher Cornell University
Subject 0604 Genetics
0601 Biochemistry and Cell Biology
Abstract Much current network analysis is predicated on the assumption that important biological networks will either possess scale free or exponential statistics which are independent of network size allowing unconstrained network growth over time. In this paper, we demonstrate that such network growth models are unable to explain recent comparative genomics results on the growth of prokaryote regulatory gene networks as a function of gene number. This failure largely results as prokaryote regulatory gene networks are “accelerating” and have total link numbers growing faster than linearly with network size and so can exhibit transitions from stationary to nonstationary statistics and from random to scale-free to regular statistics at particular critical network sizes. In the limit, these networks can undergo transitions so marked as to constrain network sizes to be below some critical value. This is of interest as the regulatory gene networks of single celled prokaryotes are indeed characterized by an accelerating quadratic growth with gene count and are size constrained to be less than about 10,000 genes encoded in DNA sequence of less than about 10 megabases. We develop two “nonaccelerating” network models of prokaryote regulatory gene networks in an endeavor to match observation and demonstrate that these approaches fail to reproduce observed statistics.
Keyword Prokaryote regulatory gene networks
Genomics
Q-Index Code CX

Document type: Journal Article
Sub-type: Article (original research)
Collections: Excellence in Research Australia (ERA) - Collection
Institute for Molecular Bioscience - Publications
 
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Created: Wed, 17 Mar 2010, 11:18:33 EST by Michael Affleck on behalf of Institute for Molecular Bioscience