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The Biomedical Informatics Research Network

2008·54 Zitationen·The MIT Press eBooks
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54

Zitationen

5

Autoren

2008

Jahr

Abstract

compute-intensive distributed collaborations in biomedical science with information technology innovations (Grethe et al. 2005; Ellisman and Peltier 2004). 1 Currently, BIRN is composed of a collection of three scientific collaboratories centered around the brain imaging and genetics of human neurological disorders and the associated animal models. To enable these collaborative groups, the BIRN Coordinating Center (BIRN-CC) was established to develop, implement, and support the infrastructure necessary to achieve the large-scale data sharing, computation, and collaboration among the scientific collaboratories. BIRN’s overriding goal is to collect data from a number of researchers at different institutions so that for each scientific investigation, the scientists can consider sample sizes in the hundreds or thousands instead of in the tens. This is especially important in research into the causes and cures for relatively rare diseases. The BIRN collaboratories are: n Function BIRN: Developing multisite functional magnetic resonance (MR) tools focusing on understanding the underlying causes of schizophrenia and treatments for the disease. n Brain Morphometry BIRN: Developing calibration and anatomical analysis tools to investigate the structural variance among brains with an eye to correlating specific structural differences to symptoms such as memory dysfunction or depression. n Mouse BIRN: Focusing on mouse models of human disease, such as multiple sclerosis, schizophrenia, Parkinson’s disease, attention deficit hyperactive disorder, Tourette’s syndrome, and brain cancer. These researchers are aggregating data from different scales, from molecular information to anatomical imaging, to better understand these neurological disorders. n BIRN-CC: Focusing on common technological issues across the various BIRN collaboratories,

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Biomedical and Engineering EducationScientific Computing and Data ManagementElectronic Health Records Systems
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