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 …

Date

2015

Authors

Arthur W Toga, Ian Foster, Carl Kesselman, Ravi Madduri, Kyle Chard, Eric W Deutsch, Nathan D Price, Gustavo Glusman, Benjamin D Heavner, Ivo D Dinov, Joseph Ames, John Van Horn, Roger Kramer, Leroy Hood

Journal

Journal of the American Medical Informatics Association

Volume

22

Issue

6

Pages

1126-1131

Publisher

Oxford University Press