Codet: An Easy-To-Use Community Detection Tool

Network data plays an important role in biological research. For example, the interaction between proteins in living cells forms large complex networks. The corporation of cells in a living body also makes up networks. As an important approach to analysing the topology of network data, community detection methods have attracted a great interest of researchers, and different algorithms have been developed during the past decade. However, the diversity of these algorithms also makes users confused to choose a suitable one according to the specific application. In this paper, we present CoDeT, a system which integrates 11 state-of-the-art community detection algorithms and 12 recognised metrics, to address the difficulty. Especially, CoDeT is capable to recommend the most suitable algorithm for users when they consider multiple algorithms for a given data set. Experimental results show that the recommended algorithms by our system are effective on bioinformatic networks. In addition, with our provided C++, Python and web service interfaces, users can easily select the most convenient one to start their experience.