A computer visualization of a river bed created using VisTrails, a system developed by University of Utah computer scientists to help scientists create high-quality visualizations. Under the CluE initiative, the University of Utah team will work with other computer scientists from the University of Washington to expand the capabilities of VisTrails and make it easier to visualize very large data sets.

Credit: Juliana Freire and Claudio Silva, University of Utah

In this interview, Mihai Pop, an assistant professor of computer science at the University of Maryland, discusses his research as part of the CluE initiative between Google, IBM and NSF. His research focuses on developing parallel algorithms for analyzing the next generation of sequencing data. Scientists can now generate the rough equivalent of an entire human genome in just a few days with one single sequencing instrument. The analysis of these data is complicated by their size - a single run of a sequencing instrument yields terabytes of information, often requiring a significant scale-up of the existing computational infrastructure needed for analysis.

Credit: National Science Foundation

Visualizations have played an important role in science for decades. As data collection becomes more sophisticated, finding ways to visualize large data sets in a relatively easy and affordable manner has become an imperative. As part of the CluE initiative, Bill Howe, a computer scientist at the University of Washington, is working with colleagues at the University of Utah to develop a cost-effective visualization tool based on the VisTrails suite.

Credit: University of Washington and the National Science Foundation.