Visualizing biological data in google earth

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. Biologists interested in a species may want to see all hundreds of metabolic pathways for that species. Instead of simply showing hundreds of pathways in one network in a complex and incomprehensible graph, MetNetGE organizes those pathways based on the hierarchical pathway ontology, and visualizes the structure using the proposed 3D Enhanced Radial Space-Filling (ERSF) technique. The ERSF algorithm uses an orbit metaphor to present the non-tree edges in the ontology. Mapping cumulative omics statistics on the ERSF drawing aids biologists in easily identifying highly activated pathways or categories in an experiment. MetNetGE uses Google Earth (GE) as the underlining visualization tool. All the biological entities are converted to objects in the KML (Keyhole Markup Language) file and loaded in GE. 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. Results showed that the completion time of using MetNetGE is about half of using Cytoscape.