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Data-intensive computing laying foundation for biological breakthroughs

Researchers in the Biopilot project are developing new and innovative software to help solve data-intensive computational problems in biological research.

Biological breakthroughs to solve society’s most challenging problems require innovative tools and a “different way” to analyze the enormous amounts of data being generated.

Finding this way is the goal of the Data-Intensive Computing for Complex Biological Systems (Biopilot) project—a joint research effort between the Pacific Northwest National Laboratory and Oak Ridge National Laboratory funded by the Department of Energy’s Office of Advanced Scientific Computing Research. The two national laboratories are teaming to support areas of biological research in urgent need of data-intensive computing capabilities. Recent advances in high-throughput technologies have generated an explosion of biological data. “Conventional software isn’t able to efficiently deal with such massive data sets,” said project lead T.P. Straatsma, a PNNL senior scientist. The Biopilot project is developing innovative and robust software solutions to address large-scale, data-intensive computational problems in biology and to make these new capabilities available to the biology community.

“To really understand biological systems, we must integrate its complex networks and pathways for a coherent understanding of the system,” Straatsma said. “The more different types of data you can integrate, the deeper are the biological insights. Our goal is to create an integrated suite of highly flexible, very adaptable computational tools for large-scale data sets that will be used to address specific challenges facing DOE and our society.”

Researchers in the Biopilot project are focusing on three areas: peptide protein identification and quantification algorithms for mass-spectrometry proteomics, massively parallel solutions for high-throughput comparative genomics, and large-scale integration of molecular and network modeling and simulation with bioinformatics approaches.

“The ability to process and analyze massive amounts of data and information in real time is powerful in making breakthroughs and solving complex problems,” Straatsma said. “The Biopilot project will play a major role.”



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