The interplay between microscopic and mesoscopic structures in complex networks.

ABSTRACT: Understanding a complex network's structure holds the key to understanding its function. The physics community has contributed a multitude of methods and analyses to this cross-disciplinary endeavor. Structural features exist on both the microscopic level, resulting from differences between single node properties, and the mesoscopic level resulting from properties shared by groups of nodes. Disentangling the determinants of network structure on these different scales has remained a major, and so far unsolved, challenge. Here we show how multiscale generative probabilistic exponential random graph models combined with efficient, distributive message-passing inference techniques can be used to achieve this separation of scales, leading to improved detection accuracy of latent classes as demo

SUBMITTER: Reichardt J 

PROVIDER: S-EPMC3148213 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature