HPCwire: PNNL Researchers Earn Top Honors at SC08

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December 03, 2008

PNNL Researchers Earn Top Honors at SC08

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Interactive program that can search through DNA wins contest

RICHLAND, Wash., Dec. 3 -- DNA sequencing is easier than ever, but the amount of data to be analyzed is piling up. An award-winning computer program now shows that genome sequence analysis can be made interactive and intuitive, helping researchers find hidden relationships in massive amounts of data.

Researchers from the Department of Energy's Pacific Northwest National Laboratory captured "Best Overall" for their entry at the Supercomputing '08 High Performance Computing Analytics Challenge in Austin, Texas, on Nov. 20.

In the competition, scientists were judged on solving real world problems using comprehensive computational approaches, large data sets, and high-end visualization technology to display results -- which means it had to look good and be easy to use.

PNNL's Chris Oehmen led a multidisciplinary team composed of Scott Dowson, Chandrika Sivaramakrishnan, Justin Almquist, Lee Ann McCue, Bobbie-Jo Webb-Robertson, and Jason McDermott to the win. The team used resources at PNNL and at EMSL, DOE's Environmental Molecular Sciences Laboratory on the PNNL campus, to develop the interactive program.

Past finalists have been in areas as varied as orthodontics, atomic energy, and music classification. PNNL's winning entry in genomics combined multiple databases, analysis software, and a home-grown "visualization technology" called Starlight that presents data in unique visual patterns and allows users to interactively explore them.

"Our entire team is thrilled that we won," Oehmen said. "It's an honor to be a part of this international competition. We could not have completed the challenge without the support of our sponsors at the Department of Energy, the National Science Foundation, and internal investments from the Pacific Northwest National Laboratory."

A common problem for genomics researchers, said Oehmen, is that desktop computers often can't handle the volume of calculations needed to analyze many genomes at once. At the other end of the spectrum, high performance computers often limit researchers' ability to guide the analysis along the way.

"We wanted to demonstrate that high-performance computing can be integrated into an iterative workflow because this is the way biologists really work," Oehmen said. "It was the MeDICi middleware that really helped us pull the various data, analysis, and visualization together."

In genomic studies, computer programs compare DNA sequences of different living things to find shared proteins or uncover the function of a mystery protein, generating ideas that can then be tested in laboratory experiments. This interactive program gives laboratory researchers a place to start in looking for proteins and genes with interesting functions.

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