@inproceedings{791ff82e619147c6b0be89705dca1f8b,
title = "Galaxy cluster to cloud-Genomics at scale",
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.",
author = "{The Galaxy Team} and Enis Afgan and Dannon Baker and John Chilton and Nate Coraor and James Taylor",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 9th Gateway Computing Environments Workshop, GCE 2014 ; Conference date: 21-11-2014",
year = "2015",
month = jan,
day = "23",
doi = "10.1109/GCE.2014.13",
language = "English (US)",
series = "Proceedings of GCE 2014: 9th Gateway Computing Environments Workshop, held in conjunction with SC 2014: The International Conference for High Performance Computing, Networking, Storage and Analysis",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "47--50",
booktitle = "Proceedings of GCE 2014",
address = "United States",
}