PathInHydro, a Set of Machine Learning Models to Identify Unbinding Pathways of Gas Molecules in [NiFe] Hydrogenases


Journal article


Farzin Sohraby, Jing-Yao Guo, Ariane Nunes-Alves
Journal of Chemical Information and Modeling, vol. 65, 2025, pp. 589-602


Cite

Cite

APA   Click to copy
Sohraby, F., Guo, J.-Y., & Nunes-Alves, A. (2025). PathInHydro, a Set of Machine Learning Models to Identify Unbinding Pathways of Gas Molecules in [NiFe] Hydrogenases. Journal of Chemical Information and Modeling, 65, 589–602. https://doi.org/10.1021/acs.jcim.4c01656


Chicago/Turabian   Click to copy
Sohraby, Farzin, Jing-Yao Guo, and Ariane Nunes-Alves. “PathInHydro, a Set of Machine Learning Models to Identify Unbinding Pathways of Gas Molecules in [NiFe] Hydrogenases.” Journal of Chemical Information and Modeling 65 (2025): 589–602.


MLA   Click to copy
Sohraby, Farzin, et al. “PathInHydro, a Set of Machine Learning Models to Identify Unbinding Pathways of Gas Molecules in [NiFe] Hydrogenases.” Journal of Chemical Information and Modeling, vol. 65, 2025, pp. 589–602, doi:10.1021/acs.jcim.4c01656.


BibTeX   Click to copy

@article{sohraby2025a,
  title = {PathInHydro, a Set of Machine Learning Models to Identify Unbinding Pathways of Gas Molecules in [NiFe] Hydrogenases},
  year = {2025},
  journal = {Journal of Chemical Information and Modeling},
  pages = {589-602},
  volume = {65},
  doi = {10.1021/acs.jcim.4c01656},
  author = {Sohraby, Farzin and Guo, Jing-Yao and Nunes-Alves, Ariane}
}