Mar 1, 2016

New BD2K training grant in Bio-Data Science

Problems in the generation, acquisition, management, analysis, visualization, and interpretation, of data, which have always been important players in biomedical science, now assume leading roles in the massive effort to understand health and disease. The unprecedented size, complexity, and heterogeneity of big biomedical data demands research that will allow us to more efficiently extract knowledge from data in order to make better predictions, to characterize biological systems, and generally to enable subsequent investigation. Modern biological, medical, and health studies often involve data sets from which useful, accurate information cannot be efficiently extracted with available methods. 

Research to improve the analysis of big biomedical data is active at the interface of computer sciences, statistics, and various biomedical disciplines, including genomics, molecular biology, neuroscience, cancer research, and population health.  The mission of the Bio-Data Science (BDS) training program is to provide predoctoral research training at this interface, preparing graduate students for key roles in academia, industry, or government. The BDS training program is supported by a T32 grant from the National Library of Medicine, and will be tightly integrated with the activities of the Center for Predictive Computational Phenotyping.

Dec 1, 2015

MIR Blue Sky Science: What is Machine Learning?

The Morgridge Institute for Research, a partner in CPCP, produces a weekly Q&A series that gives children and adults a forum to pose curiosity-driven, blue-sky questions about science. The public poses the questions and the Blue Sky Science team finds the relevant Madison scientists to answer the questions.  In this edition, CPCP Investigator Rob Nowak answers the question "What is machine learning?"

Oct 19, 2015

Big Privacy: Policy Meets Data Science

On October 15, 2015 CPCP held the first symposium in new annual series focusing on the intersection of policy and bioethics with biomedical research utilizing big data.  The half-day symposium examined the legal, policy, and technical issues arising where data privacy and data science meet. 

With the advent of high-throughput methods in biomedical research, the drive for precision medicine, and the advances in computing and mathematics that foster “big data science,” many commentators have expressed concern about how to promote biomedical science while respecting people’s privacy. The same big data techniques that promise revolutionary medical breakthroughs also make it easier to figure out whose data are being used in research and to learn sensitive information about those people.

As the only member of the NIH Big Data to Knowledge consortium including a bioethicist as a member of its investigator team, CPCP will host an annual symposium addressing current and emerging facets of the critical issue of privacy and make the proceedings available to the consortium via webcast and video.

Jun 25, 2015

Campus ‘Big Data’ project may point the way to Alzheimer’s early detection

“The idea of predictive phenotyping is really critical for this
disease,” says Johnson. “If we could catch Alzheimer’s early and
postpone it even by 10 years, those 14 million cases we are projecting
could be reduced to 3.5 million cases – a 75 percent reduction.”

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