Galaxy-ML : : an accessible, reproducible, and scalable machine learning toolkit for biomedicine
Abstract: Supervised machine learning is an essential but difficult to use approach in biomedical data analysis. The Galaxy-ML toolkit (https://galaxyproject.org/community/machine-learning/) makes supervised machine learning more accessible to biomedical scientists by enabling them to perform end-to-end reproducible machine learning analyses at large scale using only a web browser. Galaxy-ML extends Galaxy (https://galaxyproject.org), a biomedical computational workbench used by tens of thousands of scientists across the world, with a suite of tools for all aspects of supervised machine learning
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Edition
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Version 2
- Language
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Englisch
- Notes
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PLOS computational biology. - 17, 6 (2021) , e1009014, ISSN: 1553-7358
- Event
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Veröffentlichung
- (where)
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Freiburg
- (who)
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Universität
- (when)
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2024
- Creator
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Gu, Qiang
Kumar, Anup
Bray, Simon A.
Creason, Allison
Khanteymoori, Alireza
Jalili, Vahid
Grüning, Björn
Goecks, Jeremy
- DOI
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10.1371/journal.pcbi.1009014
- URN
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urn:nbn:de:bsz:25-freidok-2478148
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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25.03.2025, 1:42 PM CET
Data provider
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Gu, Qiang
- Kumar, Anup
- Bray, Simon A.
- Creason, Allison
- Khanteymoori, Alireza
- Jalili, Vahid
- Grüning, Björn
- Goecks, Jeremy
- Universität
Time of origin
- 2024