Hierarchical Network Structure Promotes Dynamical Robustness
Abstract
The relationship between network topology and system dynamics has significant implications for unifying our understanding of the interplay among metabolic, generegulatory, and ecosystem network architecures. Here we analyze the stability and robustness of a large class of dynamics on such networks. We determine the probability distribution of robustness as a function of network topology and show that robustness is classified by the number of links between modules of the network. We also demonstrate that permutation of these modules is a fundamental symmetry of dynamical robustness. Analysis of these findings leads to the conclusion that the most robust systems have the most hierarchical structure. This relationship provides a means by which evolutionary selection for a purely dynamical phenomenon may shape network architectures across scales of the biological hierarchy.
 Publication:

arXiv eprints
 Pub Date:
 December 2014
 DOI:
 10.48550/arXiv.1412.0709
 arXiv:
 arXiv:1412.0709
 Bibcode:
 2014arXiv1412.0709S
 Keywords:

 Quantitative Biology  Populations and Evolution;
 Nonlinear Sciences  Chaotic Dynamics;
 Physics  Data Analysis;
 Statistics and Probability;
 Quantitative Biology  Molecular Networks
 EPrint:
 23 pages, 9 figures, 2 tables