Polaris Challenge: Data-Driven Priors to Improve Docking for Pose Prediction

Kunyang Sun, Yingze Wang, Justin Purnomo, Teresa Head-Gordon

Open source

DOI: 10.1021/acs.jcim.5c01976
Published: 2025-10-28
Container: Journal of Chemical Information and Modeling
Publisher: American Chemical Society (ACS)
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1021/acs.jcim.5c01976,
  title = {Polaris Challenge: Data-Driven Priors to Improve Docking for Pose Prediction},
  author = {Kunyang Sun and Yingze Wang and Justin Purnomo and Teresa Head-Gordon},
  year = {2025},
  journal = {Journal of Chemical Information and Modeling},
  doi = {10.1021/acs.jcim.5c01976},
  url = {https://doi.org/10.1021/acs.jcim.5c01976}
}

RIS

TY  - JOUR
TI  - Polaris Challenge: Data-Driven Priors to Improve Docking for Pose Prediction
AU  - Kunyang Sun
AU  - Yingze Wang
AU  - Justin Purnomo
AU  - Teresa Head-Gordon
PY  - 2025
JO  - Journal of Chemical Information and Modeling
DO  - 10.1021/acs.jcim.5c01976
UR  - https://doi.org/10.1021/acs.jcim.5c01976
ER  -

APA

Sun, K., Wang, Y., Purnomo, J., & Head-Gordon, T. (2025). Polaris Challenge: Data-Driven Priors to Improve Docking for Pose Prediction. Journal of Chemical Information and Modeling. https://doi.org/10.1021/acs.jcim.5c01976

Source records

crossref · retrieved 2026-09-27T07:49:27.839Z