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Meaningful visualization of large scale biological data is the key for achieving new discoveries in system biology research. Typical types of biological data in research includes: biological pathways or networks, biological ontologies, and experimental data. Visualization tools used in these areas often fail to present a meaningful and insightful view of underlining data. We present a new interactive visualization tool, MetNetGE, which features novel visualization techniques for three kinds of biological data: pathway, ontology and omics data. For a given biological pathway, we proposed a novel 3D layout algorithm, aligned 3D tiered layout, which arrange the pathway nodes into different tiers to make the cross- layer connection patterns stand out. A user study with 20 participants to demonstrate the improved efficiency of MetNetGE over Cytoscape regards certain biological tasks. Although MetNetGE requires higher learning time (680 seconds vs. 350 seconds) on average, it helps participants quickly finish the tasks.

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Ming Jia attended Tsinghua University, got both his bachelor and master degree in Electrical Engineering. He then join Iowa State University for PhD research supervised by Prof. Julie Dickerson. His main research area is biological data visualization, especially in pathway and ontology data.

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