4.1 Article

SIMON: Open-Source Knowledge Discovery Platform

期刊

PATTERNS
卷 2, 期 1, 页码 -

出版社

CELL PRESS
DOI: 10.1016/j.patter.2020.100178

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资金

  1. NIHR Birmingham Biomedical Research Centre at the University Hospitals Birmingham NHS Foundation Trust
  2. University of Birmingham
  3. NIH [U19 AI057229]
  4. Howard Hughes Medical Institute
  5. EU's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant (FluPRINT) [796636]
  6. Marie Curie Actions (MSCA) [796636] Funding Source: Marie Curie Actions (MSCA)

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SIMON, a modular open-source software, offers a convenient solution for non-technical and technical researchers to apply over 180 state-of-the-art machine-learning algorithms to high-dimensional biomedical data. Its user-friendly interface, standardized pipelines, and automated machine learning methods help users identify optimal algorithms efficiently.
Data analysis and knowledge discovery has become more and more important in biology and medicine with the increasing complexity of biological datasets, but the necessarily sophisticated programming skills and indepth understanding of algorithms needed pose barriers to most biologists and clinicians to perform such research. We have developed a modular open-source software, SIMON, to facilitate the application of 180+ state-of-the-art machine-learning algorithms to high-dimensional biomedical data. With an easy-touse graphical user interface, standardized pipelines, and automated approach for machine learning and other statistical analysis methods, SIMON helps to identify optimal algorithms and provides a resource that empowers non-technical and technical researchers to identify crucial patterns in biomedical data.

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