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AKB: Biologische Physik

AKB 30: Poster Session I

AKB 30.15: Poster

Montag, 27. März 2006, 15:30–18:00, P1

Offdiagonal Complexity: Characterizing graph complexity from nondiagonal link correlations - Application to biological networks — •Jens Christian Claussen — Institut für Theoretische Physik und Astrophysik, Christian-Albrecht-Universität Kiel, Germany

A vast variety of biological, social, and economical networks shows topologies drastically differing from random graphs; yet the quantitative characterization of their “complexity” remains unsatisfactory from a conceptual point of view. Motivated from the discussion of small scale-free networks, a biased link distribution entropy is defined, which takes an extremum for a power law distribution. This approach is extended to the node-node link cross-distribution, whose nondiagonal elements characterize the graph structure beyond link distribution, cluster coefficient and average path length. From here a simple (and computationally cheap) complexity measure can be defined [1]. This approach is applied to a protein interaction network in comparison to randomized surrogates, and to the spatial evolution of a cell aggregate adjacency matrix as a function of time [2].

[1] J.C. Claussen, arXiv.org e-print q-bio/0410024

[2] J.C. Claussen, Offdiagonal complexity: A computationally quick network complexity measure. Application to protein networks and cell division (submitted)