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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.An online demo video of MC-Explorer can be accessed from https://www.dropbox.com/s/vkalumc28wqp8yl/demo.mov.

Original languageEnglish (US)
Title of host publicationProceedings - 2020 IEEE 36th International Conference on Data Engineering, ICDE 2020
PublisherIEEE Computer Society
Pages1722-1725
Number of pages4
ISBN (Electronic)9781728129037
DOIs
StatePublished - Apr 2020
Event36th IEEE International Conference on Data Engineering, ICDE 2020 - Dallas, United States
Duration: Apr 20 2020Apr 24 2020

Publication series

NameProceedings - International Conference on Data Engineering
Volume2020-April
ISSN (Print)1084-4627

Conference

Conference36th IEEE International Conference on Data Engineering, ICDE 2020
CountryUnited States
CityDallas
Period4/20/204/24/20

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Information Systems

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  • Cite this

    Li, B., Cheng, R., Hu, J., Fang, Y., Ou, M., Luo, R., Chang, K. C. C., & Lin, X. (2020). MC-Explorer: Analyzing and visualizing motif-cliques on large networks. In Proceedings - 2020 IEEE 36th International Conference on Data Engineering, ICDE 2020 (pp. 1722-1725). [9101676] (Proceedings - International Conference on Data Engineering; Vol. 2020-April). IEEE Computer Society. https://doi.org/10.1109/ICDE48307.2020.00154