Explainable machine learning models enhance prediction of PFAS bioactivity using quantitative molecular surface analysis-derived representation Article

Yin, Zhipeng, Zhang, Min, Liu, Runzeng et al. (2025). Explainable machine learning models enhance prediction of PFAS bioactivity using quantitative molecular surface analysis-derived representation . WATER RESEARCH, 280 10.1016/j.watres.2025.123500

cited authors

  • Yin, Zhipeng; Zhang, Min; Liu, Runzeng; Cai, Yong

authors

publication date

  • July 15, 2025

published in

keywords

  • DERIVATIVES
  • Engineering
  • Engineering, Environmental
  • Environmental Sciences
  • Environmental Sciences & Ecology
  • Life Sciences & Biomedicine
  • Machine learning
  • Molecular dynamics simulation
  • Molecular representation
  • PFAS
  • Physical Sciences
  • Risk assessment
  • Science & Technology
  • TOXICITY
  • Technology
  • Water Resources

Digital Object Identifier (DOI)

publisher

  • PERGAMON-ELSEVIER SCIENCE LTD

volume

  • 280