SCDA: A New Direction for Data Analysis

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bigdata

SCDA will create innovative ways to examine and access large-scale data sets.

The Simons Center for Data Analysis (SCDA), launched in 2013, was formed to develop new and innovative methods of examining data whose scale and complexity have historically resisted analysis.

While problems of interest to SCDA might come from any number of fields, the initial focus of the center will be on genomics and neuroscience. Currently, the data sets targeted for use by SCDA include neurophysiological data from multi-electrode recordings, imaging data from microscopy, and genomic/proteomic data from various high-throughput technologies.

“We are particularly interested in problems that present mathematical and computational challenges, requiring a concerted long-term research effort, where we could make a real impact,” says Leslie Greengard, the center’s founding director.

In addition to the development of new analysis tools, says Greengard, SCDA plans to create systems that provide researchers with access to domain-specific, large-scale data sets, together with state-of-the-art software. “Ultimately,” Greengard explains, “our goal is the creation of tools that can help us learn about the underlying principles of biological organization, develop new diagnostic approaches to disease and identify new targets for therapeutics.”

In the early stages of the center’s development, Greengard will build and lead a team composed of mathematicians, computer scientists, statisticians, bioinformatics researchers, computational biologists and neuroscientists.

“It is widely recognized that mathematical and computational modeling are critical for organizing and exploring the vast amounts of information that are becoming available,” says Greengard. “SCDA has the potential to play a unique role: helping scientists in multiple disciplines to share their data and creating powerful, new analytic methods, both of which can accelerate the research process and make results more easily reproducible.”

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  • I am particularly interested to learn about the contribution of computer science/data to bio-science.

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