NetGestalt: integrating multidimensional omics data over biological networks

Jing Wang, Zhiao Shi, Bing Zhang

Biological networks have become a valuable model for the visualization and integration of different types of omics data. However, traditional node-link diagram based network visualization becomes inadequate as network size and data complexity increase. Here we present NetGestalt (, a novel web-based data integration framework that transforms the traditional two-dimensional depiction of networks into a scalable one-dimension representation by exploiting the inherent hierarchical modular organization of biological networks. Thus, the framework allows simultaneous presentation of large-scale experimental and annotation data from various sources in the context of a biological network to facilitate data visualization, analysis, interpretation, and hypothesis generation. For enhanced user experience, NetGestalt employs efficient software architecture to enable fast rendering and smooth navigation at scales ranging from individual genes to the whole network. By applying NetGestalt to different types of cancer genomic data, we demonstrate its potential in revealing important biological insights that cannot be readily obtained with existing visualization tools.

BioVis 2013 Information

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