Network module (community) structure has been a hot research topic in recent years. Many methods have been proposed for module detection and identification. Hierarchical structure of modules is shown to exist in many networks such as biological networks and social networks. Compared to the partitional module identification methods, less research is done on the inference of hierarchical modular structure. In this paper, we propose a method for constructing the hierarchical modular structure based on the stochastic block model. Statistical tests are applied to test the hierarchical relations between different modules. We give both artificial networks and real data examples to illustrate the performance of our approach. Application of the proposed method to yeast gene coexpression network shows that it does have a hierarchical modular structure with the modules on different levels corresponding to different gene functions.

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module community structure biological networks partitional module identification artificial networks yeast gene coexpression network real data inference of hierarchical modular structure gene functions stochastic block

Shuqin Zhang,.Hierarchical Modular Structure Identification with Its Applications in Gene Coexpression Networks. 2012 (),.

Shuqin Zhang,"Hierarchical Modular Structure Identification with Its Applications in Gene Coexpression Networks" 2012

Shuqin Zhang,"Hierarchical Modular Structure Identification with Its Applications in Gene Coexpression Networks"