3D Visualization of Renal Gene Clusters
Despite the availability of numerous tools to visualize networks in three dimensions, and cognitive experiments showing improved performance with such tools, few studies have demonstrated their practical value for revealing novel insights. This project focused on the use of immersive technologies to reveal hidden irregularities in dense network clusters.
Through the use of the Virtual Reality CAVE and several in-house customizations and additions to the UM3D Lab's Jugular engine, researchers were able to step inside the vast datasets and explore them in a unique and intuitive way. The ability to navigate through the dataset and observe it from any vantage point in full 3D led to new discovers which were missed when viewing the same dataset on a laptop monitor.
The datasets were initially solved using Pajek, a common program for network visualization. The resulting file was then interpretted by the Jugular engine for display on the University of Michigan 3D Lab's many visualization technologies. Proper interpretation of the file, connection between nodes, and labeling were all challenges that have been overcome to create a natural viewing experience.
The resulting application has been used for a variety of purposes including experiments with the Kinect device.
Published Article: BMC Research Notes
Researcher: Suresh Bhavnani
Development: Ted Hall, Arunkumaar Ganesan