NIH provides $32.8 million to enhance biomedical informatics research network


Sample data from Stanford's 3T MRI system shows the global response to holding one's breath for 15 seconds. The entire gray matter volume is activated in each subject by the breath-holding task. (High-resolution image courtesy of Gary Glover and Lara Foland, Stanford University.)

Full size image available here

Bethesda, Md.--The National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH), announced today it will provide $32.8 million in additional funding to enhance its Biomedical Informatics Research Network (BIRN). The University of California San Diego Medical School will receive $18.8 million over five years, while Massachusetts General Hospital will be granted nearly $14 million for three years of support. BIRN is an NIH initiative involving a consortium of 15 universities and 22 research groups that fosters collaborations in biomedical science by utilizing information technology innovations. BIRN's initial three test bed projects focus on brain imaging of human neurological disorders and associated animal models.

"Information technology offers tremendous potential to advance our ability to diagnose and treat disease," said NCRR Director Judith L. Vaitukaitis, M.D. "BIRN's powerful and flexible approaches to data integration are designed to accommodate the dynamic nature of scientific inquiry and to allow novel discoveries that incorporate knowledge across scale and even across species. With this additional investment in the BIRN consortium, we hope to provide researchers with networked analytical tools that will greatly advance our knowledge of neurological disorders such as depression, schizophrenia, and Alzheimer's disease."

BIRN's charter is to create an environment encouraging biomedical scientists and clinical researchers to make new discoveries by facilitating sharing, analysis, visualization, and data comparisons across laboratories. A central premise of the BIRN cyberinfrastructure is that the physical location of data and resources should not hamper a research study. BIRN's data integration framework builds on the National Partnership for Advanced Computational Infrastructure, supported by the National Science Federation.

BIRN consists of four parts:

  • The Function BIRN is working to understand the underlying causes of schizophrenia and to develop new treatments for the disease. The goal is to determine the role of frontal and temporal lobe dysfunction in schizophrenia, and to assess the impact of treatments on functional brain abnormalities.

  • The Brain Morphometry BIRN is investigating whether brain structural differences correlate to symptoms such as memory dysfunction or depression and whether specific structural differences distinguish diagnostic categories.

  • The Mouse BIRN is examining animal models of multiple sclerosis, schizophrenia, Parkinson's disease, ADHD (Attention-Deficit Hyperactivity Disorder), Tourette's Syndrome and brain cancer. Researchers are studying animal models of disease at different anatomical scales to test hypotheses associated with human neurological disorders.

  • The BIRN Coordinating Center (BIRN-CC) develops, implements, and supports the information technology infrastructure necessary to achieve distributed collaborations and data sharing among the test bed participants.

Although all three test beds involve some aspect of neuroimaging, the problems that they are addressing are common throughout biomedical research and the solutions will be applicable outside the individual fields represented in the test beds. For example, BIRN is using these initial test bed studies to drive the construction and daily use of a federated data sharing environment that presents biological data held at geographically separate sites as a single, unified database. To this end, the BIRN program is rapidly producing tools and technologies that enable the aggregation of data from virtually any laboratory's research program to the BIRN data federation system, independent of the biological problem being addressed.

Lessons learned and best practices are continuously collected and made available to help new collaborative efforts make efficient use of this infrastructure at an increasingly rapid pace. These tools and best practices are intended to maximize the extent to which the infrastructure being developed can quickly be deployed to support the greater biomedical research community.

Source: Eurekalert & others

Last reviewed: By John M. Grohol, Psy.D. on 21 Feb 2009
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