Recent years have witnessed the development of a large body of algorithms for community
detection in complex networks. Most of them are based upon the optimization of objective …

We present Knowledge Engine for Genomics (KnowEnG), a free-to-use computational
system for analysis of genomics data sets, designed to accelerate biomedical discovery. It …

We investigate properties that intuitively ought to be satisfied by graph clustering quality
functions, that is, functions that assign a score to a clustering of a graph. Graph clustering …

Finding communities or clusters in social networks is a famous topic in social network
analysis. Most algorithms are limited to static snapshots so they cannot handle dynamics …

Complex networks considering both positive and negative links have gained considerable
attention during the past several years. Community detection is one of the main challenges …

Specialized processing in the brain is performed by multiple groups of brain regions
organized as functional modules. Although, in vivo studies of brain functional modules …

An essential component of a botnet is the Command and Control (C2) channel (a network).
The mechanics of C2 establishment often involve the use of structured overlay techniques …

Automatic discovery of community structures in complex networks is a fundamental task in
many disciplines, including physics, biology, and the social sciences. The most used …

The detection of protein complexes is an essential NP-hard problem in protein-protein
interaction networks (PPI). Modularity, community score, ratio cut, and internal density are …

Graph clustering is widely used in analysis of biological networks, social networks and etc.
For over a decade many graph clustering algorithms have been published, however a …