A novel computational machine learning pipeline to quantify similarities in 3D protein structures

Shreyas U Hirway, Xiao Xu, Fan Fan

Open source

DOI: 10.1093/toxsci/kfaf007
Published: 2025-01-17
Container: Toxicological Sciences
Publisher: Oxford University Press (OUP)
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1093/toxsci/kfaf007,
  title = {A novel computational machine learning pipeline to quantify similarities in 3D protein structures},
  author = {Shreyas U Hirway and Xiao Xu and Fan Fan},
  year = {2025},
  journal = {Toxicological Sciences},
  doi = {10.1093/toxsci/kfaf007},
  url = {https://doi.org/10.1093/toxsci/kfaf007}
}

RIS

TY  - JOUR
TI  - A novel computational machine learning pipeline to quantify similarities in 3D protein structures
AU  - Shreyas U Hirway
AU  - Xiao Xu
AU  - Fan Fan
PY  - 2025
JO  - Toxicological Sciences
DO  - 10.1093/toxsci/kfaf007
UR  - https://doi.org/10.1093/toxsci/kfaf007
ER  -

APA

Hirway, S. U., Xu, X., & Fan, F. (2025). A novel computational machine learning pipeline to quantify similarities in 3D protein structures. Toxicological Sciences. https://doi.org/10.1093/toxsci/kfaf007

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crossref · retrieved 2026-09-24T23:08:44.150Z