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
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;
Conference_Titel :
Gateway Computing Environments Workshop (GCE), 2014 9th
Conference_Location :
New Orleans, LA
DOI :
10.1109/GCE.2014.13