Biomedical researchers are beginning to tap into a gold mine of nontraditional sources of data to unravel some of the complexities of human diseases.
With biomedical scientists struggling to collect and analyze millions of gigabytes of data in their efforts to improve human health, the National Institutes of Health has launched a $700 million project to develop a common data-sharing framework and start training future scientists to tap that gold mine of information. That’s the topic of a story in the current edition of Chemical & Engineering News (C&EN), the weekly newsmagazine of the American Chemical Society, the world’s largest scientific society.
Britt E. Erickson, C&EN senior editor, explains that biomedical researchers are beginning to tap into a gold mine of nontraditional sources of data to unravel some of the complexities of human diseases. That’s especially true for common diseases for which there is significant interplay between genetic variants and environmental stressors. But there is so much data being generated from so many different disciplines that it is a challenge to integrate it all.
The story describes a plan from the NIH, called Big Data to Knowledge, to bring all of the data together into one common data-sharing framework that is easily accessible by researchers. Universities will train students in data sciences so that they can better access and process the data. The integration of all of the data will allow for improved efficiency in research to help treat and cure some of the world’s diseases, the story states.
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