Stochastic blockmodeling of the modules and core of the Caenorhabditis elegans connectome.

ABSTRACT: Recently, there has been much interest in the community structure or mesoscale organization of complex networks. This structure is characterised either as a set of sparsely inter-connected modules or as a highly connected core with a sparsely connected periphery. However, it is often difficult to disambiguate these two types of mesoscale structure or, indeed, to summarise the full network in terms of the relationships between its mesoscale constituents. Here, we estimate a community structure with a stochastic blockmodel approach, the Erdős-Rényi Mixture Model, and compare it to the much more widely used deterministic methods, such as the Louvain and Spectral algorithms. We used the Caenorhabditis elegans (C. elegans) nervous system (connectome) as a model system in which biological knowle

SUBMITTER: Pavlovic DM 

PROVIDER: S-EPMC4079667 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature