Making the Most of Big Data in Biomedicine
Credit: luckey_sun on Flickr
Geisinger Health System, Penn State University and Penn State Hershey have teamed up in a $2.4-million program to train the next generation of biomedical scientists in the use of big data.
The Biomedical Big Data to Knowledge Training (B2D2K) program has been established with nearly $1.4 million in funding from the National Library of Medicine of the U.S. National Institutes of Health and more than $1 million from Penn State.
This new initiative brings together Pennsylvania data scientists, biomedical researchers and life-science researchers whose work increasingly depends on the ability to analyze, interpret and visualize very large and complex sets of data, known as "big data."
Yearly, the B2D2K program will support up to nine Penn State graduate students pursuing doctorate degrees in the realm of data analytics. Each B2D2K trainee will be mentored by faculty members with complementary expertise in data sciences and biomedical sciences.
The Penn State B2D2K program was developed by Marylyn D. Ritchie and Penn State faculty members: Vasant Honavar and Runze Li.
Ritchie, who is director of Geisinger’s Biomedical & Translational Informatics Institute and chief research informatics officer, serves as the new program's director. She is also a professor at Penn State in the Eberly College of Science Department of Biochemistry and Molecular Biology.
"Students admitted to this training program will become a new generation of scientists who can mine mountains of complex scientific data to reveal the information buried there. This will lead to advances in genetic and other types of biological and health-related research," Ritchie said.
"The program complements the informatics research initiatives of the Penn State Clinical and Translational Science Institute, which is funded by the National Institutes of Health," said Neil Sharkey, Vice President for Research at Penn State. "It also leverages Penn State's strategic investments in advanced computing infrastructure through faculty hires in the data sciences."
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