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Your Environment. Your Health.

Nick

Superfund Research Program

Nick

When it comes to telling fellow students "How I Spent My Summer," Sinnott-Armstrong, above, is sure to have one of the most interesting stories around. (Photo courtesy of Dartmouth College)


 

Nick Sinnott-Armstrong, a high-school student who completed a summer research project in the Dartmouth College Superfund Research Program (SRP), took first prize for his work in a programming contest at the Genetic and Evolutionary Computation Conference (GECCO), held July 8–12 in Montreal.


Sinnott-Armstrong worked with Casey Green and Jason Moore, Ph.D., of the NIEHS-supported Integrative Biology Core (IBC)  at Dartmouth to analyze and present epidemiological data using computer technology normally found in 3-D video games. He is the first author on a newly published paper   reporting on the application in health research.


An advanced Graphical Processing Unit, or GPU, runs an adaptation of another Dartmouth innovation — a machine learning algorithm called Multifactor Dimensionality Reduction (MDR)  . MDR was built to detect and characterize interactions among various attributes to determine predictors of a particular outcome. It has been practically applied to the analysis of gene-environment interactions in genome-wide association studies.


The technology developed by the Core directly supports research efforts within the Dartmouth SRP. "The... GPU... reduces computational time by nearly 150-fold, compared to traditional computational methods," said Moore   

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