LightGBM: An Effective and Scalable Algorithm for Prediction of Chemical Toxicity-Application to the Tox21 and Mutagenicity Data Sets

Jin Zhang, Daniel Mucs, Ulf Norinder, Fredrik Svensson. LightGBM: An Effective and Scalable Algorithm for Prediction of Chemical Toxicity-Application to the Tox21 and Mutagenicity Data Sets. Journal of Chemical Information and Computer Sciences, 59(10):4150-4158, 2019. [doi]

@article{ZhangMNS19,
  title = {LightGBM: An Effective and Scalable Algorithm for Prediction of Chemical Toxicity-Application to the Tox21 and Mutagenicity Data Sets},
  author = {Jin Zhang and Daniel Mucs and Ulf Norinder and Fredrik Svensson},
  year = {2019},
  doi = {10.1021/acs.jcim.9b00633},
  url = {https://doi.org/10.1021/acs.jcim.9b00633},
  researchr = {https://researchr.org/publication/ZhangMNS19},
  cites = {0},
  citedby = {0},
  journal = {Journal of Chemical Information and Computer Sciences},
  volume = {59},
  number = {10},
  pages = {4150-4158},
}