The National Institutes of Health today announced that The Scripps Research Institute and Scripps Translational Science Institute, both based in La Jolla, will participate in a nationwide effort to consolidate the huge amount of information generated by biomedical research.
TSRI announced it will receive a $3.8 million, four-year grant, while $600,000 will go to the STSI, which is a collaboration between TSRI and Scripps Health that works in the field of genomics.
The NIH "Big Data to Knowledge" initiative will create a dozen centers around the country to host databases of medical information, which will allow scientists and the public to mine data. TSRI and STSI will work with a center to be established at UCLA.
"Today's biomedical research is generating a huge amount of data," said Andrew Su, a TSRI associate professor and faculty member at STSI who is a co-director of the new center. "In fields such as genomics and proteomics, researchers require increasingly powerful tools to make sense of their findings and extract valuable information that could lead to improvements in human health."
Proteomics is the study of groups of proteins.
Su said the advantage of the NIH program will be that "the scientific community can build off of this centralized database, instead of having everyone reinventing the wheel" when they begin a study. He said it will be especially important for consolidating scattered information on rare diseases.
The center based at UCLA will also include participation from the University of Mississippi Medical Center, the European Bioinformatics Institute and Sage Bionetworks, a nonprofit based in Seattle.
"Data creation in today's research is exponentially more rapid than anything we anticipated even a decade ago," said NIH Director Dr. Francis Collins. "Mammoth data sets are emerging at an accelerated pace in today's biomedical research and these funds will help us overcome the obstacles to maximizing their utility. The potential of these data, when used effectively, is quite astounding."
The NIH said the challenges of making the best use of biomedical data include locating data and the appropriate software tools to access and analyze them, lack of standards for many types of data, and the research community's general lack of adopting data standards.
Other obstacles include privacy issues that can get in the way of data sharing, an unwillingness to make data available to colleagues and the expense of generating large data sets, according to the NIH.
