Tailored graph ensembles as proxies or null models for real networks II: results on directed graphs

New mathematical tools quantify the topological structure of large directed networks which describe how genes interact within a cell.

Journal of Physics A 44, 275002 (2011)

E. Roberts, T. Schlitt, A. Coolen

Tailored graph ensembles as proxies or null models for real networks II: results on directed graphs
Tailored graph ensembles as proxies or null models for real networks II: results on directed graphs
Tailored graph ensembles as proxies or null models for real networks II: results on directed graphs
Tailored graph ensembles as proxies or null models for real networks II: results on directed graphs
Tailored graph ensembles as proxies or null models for real networks II: results on directed graphs
Tailored graph ensembles as proxies or null models for real networks II: results on directed graphs
Tailored graph ensembles as proxies or null models for real networks II: results on directed graphs
Tailored graph ensembles as proxies or null models for real networks II: results on directed graphs
Tailored graph ensembles as proxies or null models for real networks II: results on directed graphs
Tailored graph ensembles as proxies or null models for real networks II: results on directed graphs
Tailored graph ensembles as proxies or null models for real networks II: results on directed graphs
Tailored graph ensembles as proxies or null models for real networks II: results on directed graphs
Tailored graph ensembles as proxies or null models for real networks II: results on directed graphs
Tailored graph ensembles as proxies or null models for real networks II: results on directed graphs
Tailored graph ensembles as proxies or null models for real networks II: results on directed graphs
Tailored graph ensembles as proxies or null models for real networks II: results on directed graphs

We generate new mathematical tools with which to quantify the macroscopic topological structure of large directed networks. This is achieved via a statistical mechanical analysis of constrained maximum entropy ensembles of directed random graphs with prescribed joint distributions for in- and out-degrees and prescribed degree–degree correlation functions. We calculate exact and explicit formulae for the leading orders in the system size of the Shannon entropies and complexities of these ensembles, and for information-theoretic distances. The results are applied to data on gene regulation networks.