Name
Abstract | ||
|---|---|---|
Biomedical data exploration requires integrative analyses of large datasets using a diverse ecosystem of tools. For more than a decade, the Galaxy project (https://galaxyproject.org) has provided researchers with a web-based, user-friendly, scalable data analysis framework complemented by a rich ecosystem of tools (https://usegalaxy.org/toolshed) used to perform genomic, proteomic, metabolomic, and imaging experiments. Galaxy can be deployed on the cloud (https://launch.usegalaxy.org), institutional computing clusters, and personal computers, or readily used on a number of public servers (e.g., https://usegalaxy.org). In this paper, we present our plan and progress towards creating Galaxy-as-a-Service-a federation of distributed data and computing resources into a panoptic analysis platform. Users can leverage a pool of public and institutional resources, in addition to plugging-in their private resources, helping answer the challenge of resource divergence across various Galaxy instances and enabling seamless analysis of biomedical data. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/CLOUD.2018.00124 | PROCEEDINGS 2018 IEEE 11TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING (CLOUD) |
Keywords | Field | DocType |
cloud bursting, data federation, service computing | Data science,Services computing,Computer science,Server,Galaxy,Biomedical computing,Frontier,Maintenance engineering,Distributed computing,Cloud computing,Scalability | Conference |
Volume | ISSN | Citations |
2018 | 2159-6190 | 1 |
PageRank | References | Authors |
0.41 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Enis Afgan | 1 | 178 | 21.83 |
| Vahid Jalili | 2 | 12 | 2.73 |
| Nuwan Goonasekera | 3 | 21 | 4.38 |
| James Taylor | 4 | 319 | 26.37 |
| Jeremy Goecks | 5 | 3 | 2.46 |