title: Big biomedical data as the key resource for discovery science.
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.
authors.affiliation: Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA toga@loni.usc.edu.
authors.forename: Arthur W
authors.initials: AW
authors.lastname: Toga
authors.affiliation: Computation Institute, University of Chicago and Argonne National Laboratory, Chicago, IL, USA.
authors.forename: Ian
authors.initials: I
authors.lastname: Foster
authors.affiliation: Information Sciences Institute, University of Southern California, Los Angeles, CA, USA.
authors.forename: Carl
authors.initials: C
authors.lastname: Kesselman
authors.affiliation: Computation Institute, University of Chicago and Argonne National Laboratory, Chicago, IL, USA.
authors.forename: Ravi
authors.initials: R
authors.lastname: Madduri
authors.affiliation: Computation Institute, University of Chicago and Argonne National Laboratory, Chicago, IL, USA.
authors.forename: Kyle
authors.initials: K
authors.lastname: Chard
authors.affiliation: Institute for Systems Biology, Seattle, WA, USA.
authors.forename: Eric W
authors.initials: EW
authors.lastname: Deutsch
authors.affiliation: Institute for Systems Biology, Seattle, WA, USA.
authors.forename: Nathan D
authors.initials: ND
authors.lastname: Price
authors.affiliation: Institute for Systems Biology, Seattle, WA, USA.
authors.forename: Gustavo
authors.initials: G
authors.lastname: Glusman
authors.affiliation: Institute for Systems Biology, Seattle, WA, USA.
authors.forename: Benjamin D
authors.initials: BD
authors.lastname: Heavner
authors.affiliation: Statistics Online Computational Resource (SOCR), UMSN, University of Michigan, Ann Arbor, MI, USA.
authors.forename: Ivo D
authors.initials: ID
authors.lastname: Dinov
authors.affiliation: Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA.
authors.forename: Joseph
authors.initials: J
authors.lastname: Ames
authors.affiliation: Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA.
authors.forename: John
authors.initials: J
authors.lastname: Van Horn
authors.affiliation: Institute for Systems Biology, Seattle, WA, USA.
authors.forename: Roger
authors.initials: R
authors.lastname: Kramer
authors.affiliation: Institute for Systems Biology, Seattle, WA, USA.
authors.forename: Leroy
authors.initials: L
authors.lastname: Hood
mesh_terms: D035843:Biomedical Research; D066264:Datasets as Topic; D006801:Humans; D009316:National Institutes of Health (U.S.); D009488:Neurosciences; D057170:Translational Research, Biomedical; D014481:United States
keywords: Alzheimer's disease (ID); BD2K; Parkinson's disease; analytics; big; big data; biomedical; data; discovery; discovery science; resource; science, neuroscience (ja)