• DocumentCode
    242834
  • Title

    Galaxy Cluster to Cloud - Genomics at Scale

  • Author

    Afgan, Enis ; Baker, Dannon ; Chilton, John ; Coraor, Nate ; Taylor, James

  • Author_Institution
    Dept. of Biol., Johns Hopkins Univ., Baltimore, MD, USA
  • fYear
    2014
  • fDate
    21-21 Nov. 2014
  • Firstpage
    47
  • Lastpage
    50
  • Abstract
    Fueled by the radically increased capacity to generate data over the past decade, the field of biomedical research has been constrained by the ability to analyze data. Galaxy, an open genomics and biomedical research platform, has been democratizing access to data analysis tools with its effective and accessible web interface. However, the scale of data and the scope of tools required have proven to be a significant challenge for any monolithic deployment of the Galaxy application. We have found that a distributed and federated approach to utilizing compute and storage resources is necessary. This paper describes the ongoing efforts in creating a ubiquitous platform capable of simultaneously utilizing dedicated as well as on-demand cloud resources.
  • Keywords
    Internet; cloud computing; data analysis; genomics; medical computing; Web interface; biomedical research platform; data analysis tools; distributed approach; federated approach; galaxy cluster; on-demand cloud resources; open genomics; storage resources; ubiquitous platform; Availability; Bioinformatics; Cloud computing; Data analysis; Educational institutions; Genomics; Logic gates; Cloud computing; data analysis; genomics; accessibility; federation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Gateway Computing Environments Workshop (GCE), 2014 9th
  • Conference_Location
    New Orleans, LA
  • Type

    conf

  • DOI
    10.1109/GCE.2014.13
  • Filename
    7021850