PLoS Computational Biology (Jun 2021)

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

DOI
https://doi.org/10.1371/journal.pcbi.1009014
Journal volume & issue
Vol. 17, no. 6
p. e1009014

Abstract

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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.