January 25, 2017 – Projects use Big Data to predict diseases, advance genomics analysis
Researchers at the University of Michigan will use Big Data and mobile technology to learn how to predict when individuals will get diseases including depression and hepatitis C, and to unlock the potential of single-cell gene sequencing under three recently funded projects.
The Michigan Institute for Data Science awarded the three interdisciplinary projects a combined $3 million under the second round of its Challenge Initiative program. The program is part of U-M’s $100 million Data Science Initiative, which was announced in September 2015.
MIDAS co-director Brian Athey, professor and chair of computational medicine and bioinformatics, said taken together, the projects show U-M researchers’ ability to advance translational science — from pure research to wide application — using Big Data.
“These projects have the potential to improve the lives of millions of people and to enhance our understanding of the basic elements of cell biology,” he said. “Plus, the data science tools and methodologies being developed by the U-M research teams will be applicable for many other fields of inquiry.”
One of the awards is for the Michigan Center for Health Analytics and Medical Prediction, which aims to improve researchers’ ability to diagnose and predict acute respiratory distress syndrome and hepatitis C.
The project is led by Brahmajee Nallamothu, professor of internal medicine, and will bring together an interdisciplinary team to find patterns over time in the massive amounts of data produced in the health care industry.
Although health care produces an extraordinary volume of information on patients as they receive care in hospitals and clinics, temporal patterns in data from individual patients or groups of patients with the same condition are frequently overlooked.