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To cite lilikoi in publications use:

Fang X, Liu Y, Ren Z, Du Y, Huang Q, Garmire LX (2020). “Lilikoi V2.0: a deep-learning enabled, personalized pathway-based R package for diagnosis and prognosis predictions using metabolomics data.” bioRxiv. doi:10.1101/2020.07.09.195677, https://doi.org/10.1101/2020.07.09.195677.

AlAkwaa FM, Yunits B, Huang S, Alhajaji H, Garmire LX (2018). “Lilikoi: an R package for personalized pathway-based classification modeling using metabolomics data.” GigaScience, 7(12). https://doi.org/10.1093/gigascience/giy136.

Corresponding BibTeX entries:

  @Article{,
    title = {Lilikoi V2.0: a deep-learning enabled, personalized
      pathway-based R package for diagnosis and prognosis predictions
      using metabolomics data},
    author = {Xinying Fang and Yu Liu and Zhijie Ren and Yuheng Du and
      Qianhui Huang and Lana X. Garmire},
    journal = {bioRxiv},
    year = {2020},
    doi = {10.1101/2020.07.09.195677},
    url = {https://doi.org/10.1101/2020.07.09.195677},
  }
  @Article{,
    title = {Lilikoi: an R package for personalized pathway-based
      classification modeling using metabolomics data},
    author = {Fadhl M. AlAkwaa and Breck Yunits and Sijia Huang and
      Hassam Alhajaji and Lana X. Garmire},
    journal = {GigaScience},
    year = {2018},
    volume = {7},
    number = {12},
    url = {https://doi.org/10.1093/gigascience/giy136},
  }

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.