The University of Michigan over five years will invest $100 million in a big data initiative with researchers seeking insights in four targeted areas—healthcare, learning analytics, social sciences, and transportation.
Improving personalized healthcare delivery is at the heart of the health sciences/medicine component of the university’s Data Science Initiative. By tapping into DNA sequencing, electronic health records and other sources of big data, U-Michigan researchers hope to translate basic research into patient care based on more precisely diagnosing an individual’s risk for certain types of diseases and coming up with the most effective medical therapies.
As part of the Data Science Initiative, U-M will hire 35 new faculty members, expand the university’s research computing capacity and strengthen its data management, storage, analytics and training resources.
“We have a substantial personalized health/precision medicine footprint here,” says Alfred Hero, Ph.D., co-director of the new Michigan Institute for Data Science, which was created under the initiative and has an interdisciplinary core faculty of 40 data scientists. “There’s roughly $10 million that will be invested for the computational infrastructure for handling very large data sets.”
For its part, researchers from U-M’s Institute for Healthcare Policy and Innovation can currently analyze 100 terabytes of anonymous health data from 113 million individuals. “What we’re seeing is the linking together of basic science with clinical research and health outcomes,” observes Brian Athey, Ph.D., co-director, Michigan Institute for Data Science. “As we get into more of the sensors that are going to be standard such as Fitbit and Apple Watch, this data will be made available and will be aggregated and linked with other sources such as electronic health records and genomic information.”
Athey notes that both structured and unstructured data will be used in the big data initiative. “We are funding data science services and consultants to help bring some structure and order to the data that’s going to be analyzed,” he says. Hero adds that some of the data structure “may not be understood even by experts” and that’s where machine learning methods come into play to “discover different groupings, categories, or hierarchical dependencies that might exist in data.”
U-M’s Data Science Initiative is part of a growing trend in higher education with colleges and universities investing millions into gathering, storing, and analyzing big data in an effort to leverage its potential for research. Earlier this year, Duke University announced that it received $9.75 million in gifts and matching funds to drive big data research across medicine, energy, social science and other challenge areas.
At U-M, Athey emphasizes that the $100 million investment is all coming from internal funding. “For the University of Michigan to invest in an interdisciplinary program of this magnitude is unprecedented,” he says, as the Office of the Provost and Office of Research are partnering with U-M’s 19 schools/colleges including the Medical School and School of Public Health.
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