MC-Explorer: Analyzing and Visualizing Motif-Cliques on Large Networks

Boxuan Li, Reynold Cheng, Jiafeng Hu, Yixiang Fang, Min Ou, Ruibang Luo, Kevin Chen-Chuan Chang, Xuemin Lin


Large networks with labeled nodes are prevalent in various applications, such as biological graphs, social networks, and e-commerce graphs. To extract insight from this rich information source, we propose MC-Explorer, which is an advanced analysis and visualization system. A highlight of MC-Explorer is its ability to discover motif-cliques from a graph with labeled nodes. A motif, such as a 3-node triangle, is a fundamental building block of a graph. A motif-clique is a complete subgraph in a network with respect to a desired higher-order connection pattern. For example, on a large biological graph, we found out some motif-cliques, which disclose new side effects of a drug, and potential drugs for healing diseases. MC-Explorer includes online and interactive facilities for exploring a large labeled network through the use of motif-cliques. We will demonstrate how MC-Explorer can facilitate the analysis and visualization of a labeled biological network. The work of MC-Explorer is accepted by ICDE 2020 demonstration track.

Online System

You can explore features of MC-Explorer here.



Prof. Reynold Cheng (ckcheng at

Boxuan Li (liboxuan at