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J Am Med Inform Assoc. 2015 Nov;22(6):1126-31. doi: 10.1093/jamia/ocv077. Epub 2015 Jul 21.

Big biomedical data as the key resource for discovery science.

Author information

1
Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA toga@loni.usc.edu.
2
Computation Institute, University of Chicago and Argonne National Laboratory, Chicago, IL, USA.
3
Information Sciences Institute, University of Southern California, Los Angeles, CA, USA.
4
Institute for Systems Biology, Seattle, WA, USA.
5
Statistics Online Computational Resource (SOCR), UMSN, University of Michigan, Ann Arbor, MI, USA.
6
Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA.

Abstract

Modern biomedical data collection is generating exponentially more data in a multitude of formats. This flood of complex data poses significant opportunities to discover and understand the critical interplay among such diverse domains as genomics, proteomics, metabolomics, and phenomics, including imaging, biometrics, and clinical data. The Big Data for Discovery Science Center is taking an "-ome to home" approach to discover linkages between these disparate data sources by mining existing databases of proteomic and genomic data, brain images, and clinical assessments. In support of this work, the authors developed new technological capabilities that make it easy for researchers to manage, aggregate, manipulate, integrate, and model large amounts of distributed data. Guided by biological domain expertise, the Center's computational resources and software will reveal relationships and patterns, aiding researchers in identifying biomarkers for the most confounding conditions and diseases, such as Parkinson's and Alzheimer's.

KEYWORDS:

Alzheimer's disease (ID); BD2K; Parkinson's disease; analytics; big; big data; biomedical; data; discovery; discovery science; resource; science, neuroscience (ja)

PMID:
26198305
PMCID:
PMC5009918
DOI:
10.1093/jamia/ocv077
[Indexed for MEDLINE]
Free PMC Article

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