Analysis commons, a team approach to discovery in a big-data environment for genetic epidemiology.

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Last Posted: Nov 02, 2017

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• Analysis commons, a team approach to discovery in a big-data environment for genetic epidemiology.  
  Brody Jennifer A et al. Nature genetics 2017 Oct 49(11) 1560-1563
• Big Data and Population Health: Focusing on the Health Impacts of the Social, Physical, and Economic Environment.  
  Hu Howard et al. Epidemiology (Cambridge, Mass.) 2017 Nov 28(6) 759-762
• Analysis commons, a team approach to discovery in a big-data environment for genetic epidemiology  
  JA Brody et al, Nat Genetics, Oct 30, 2017
• The Evolution of Patient Diagnosis From Art to Digital Data-Driven Science  
  KD Mandl et al, JAMA, Oct 26, 2017
• A Comprehensive Infrastructure for Big Data in Cancer Research: Accelerating Cancer Research and Precision Medicine.  
  Hinkson Izumi V et al. Frontiers in cell and developmental biology 2017 583
• Functional precision cancer medicine-moving beyond pure genomics.  
  Letai Anthony et al. Nature medicine 2017 Sep 23(9) 1028-1035
• IBM pitched its Watson supercomputer as a revolution in cancer care. It’s nowhere close  
  C Ross et al, Stat News, Sep 6, 2017
• Information management: Data domination  
  G Donati et al, Nature, August 30, 2017
• Clinical Trial Data as Public Goods: Fair Trade and the Virtual Knowledge Bank as a Solution to the Free Rider Problem - A Framework for the Promotion of Innovation by Facilitation of Clinical Trial Data Sharing among Biopharmaceutical Companies in the Era of Omics and Big Data.  
  Evangelatos Nikolaos et al. Public health genomics 2016 19(4) 211-9
• Big data opens a window onto wellness  
  Butte Atul J et al. Nature biotechnology 2017 Aug 35(8) 720-721
• Big data yields surprising connections between diseases  
  Science Mag, August 7, 2017
• Classification of common human diseases derived from shared genetic and environmental determinants  
  K Wang et al, Nature Genetics, August 7, 2017
• Systems and precision medicine approaches to diabetes heterogeneity: a Big Data perspective.  
  Capobianco Enrico et al. Clinical and translational medicine 2017 Dec 6(1) 23
• Building the biomedical data science workforce.  
  Dunn Michelle C et al. PLoS biology 2017 Jul 15(7) e2003082
• Building the biomedical data science workforce  
  MC Dunn et al, PLOS Comp Biol, July 2017
• Big data’s big bias: bringing noise and conflicts to US drug regulation  
  J Lenzer, BMJ, July 18, 2017

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