Email updates

Keep up to date with the latest news and content from BMC Genomics and BioMed Central.

This article is part of the supplement: Eleventh International Conference on Bioinformatics (InCoB2012): Computational Biology

Open Access Proceedings

Integration of interactive, multi-scale network navigation approach with Cytoscape for functional genomics in the big data era

Thanet Praneenararat1*, Toshihisa Takagi123 and Wataru Iwasaki14

Author affiliations

1 Department of Computational Biology, the University of Tokyo, Kashiwa, Chiba, 277-8568, Japan

2 National Bioscience Database Center, Japan Science and Technology Agency, Chiyoda, Tokyo, 102-0081, Japan

3 Center for Information Biology, National Institute of Genetics, Mishima, Shizuoka, 411-8540, Japan

4 Current address: Atmosphere and Ocean Research Institute, the University of Tokyo, Kashiwa, Chiba, 277-8564, Japan

For all author emails, please log on.

Citation and License

BMC Genomics 2012, 13(Suppl 7):S24  doi:10.1186/1471-2164-13-S7-S24

Published: 13 December 2012

Abstract

Background

The overwhelming amount of network data in functional genomics is making its visualization cluttered with jumbling nodes and edges. Such cluttered network visualization, which is known as "hair-balls", is significantly hindering data interpretation and analysis of researchers. Effective navigation approaches that can always abstract network data properly and present them insightfully are hence required, to help researchers interpret the data and acquire knowledge efficiently. Cytoscape is a de facto standard platform for network visualization and analysis, which has many users around the world. Apart from its core sophisticated features, it easily allows for extension of the functionalities by loading extra plug-ins.

Results

We developed NaviClusterCS, which enables researchers to interactively navigate large biological networks of ~100,000 nodes in a "Google Maps-like" manner in the Cytoscape environment. NaviClusterCS rapidly and automatically identifies biologically meaningful clusters in large networks, e.g., proteins sharing similar biological functions in protein-protein interaction networks. Then, it displays not all nodes but only preferable numbers of those clusters at any magnification to avoid creating the cluttered network visualization, while its zooming and re-centering functions still enable researchers to interactively analyze the networks in detail. Its application to a real Arabidopsis co-expression network dataset illustrated a practical use of the tool for suggesting knowledge that is hidden in large biological networks and difficult to be obtained using other visualization methods.

Conclusions

NaviClusterCS provides interactive and multi-scale network navigation to a wide range of biologists in the big data era, via the de facto standard platform for network visualization. It can be freely downloaded at http://navicluster.cb.k.u-tokyo.ac.jp/cs/ webcite and installed as a plug-in of Cytoscape.