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Galaxy-ML: An accessible, reproducible, and scalable machine learning toolkit for biomedicine

Qiang Gu, Anup Kumar, Simon Bray, Allison Creason, Alireza Khanteymoori, Vahid Jalili, Björn Grüning, Jeremy Goecks

2021PLoS Computational Biology35 citationsDOIOpen Access PDF

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.

Topics & Concepts

WorkbenchMachine learningComputer scienceSuiteArtificial intelligenceScalabilityBiomedicineBioinformaticsVisualizationBiologyDatabaseArchaeologyHistoryGenetics, Bioinformatics, and Biomedical ResearchCell Image Analysis TechniquesArtificial Intelligence in Healthcare
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