Evaluating Molecular Representations for Predicting Cyclodextrin-PFAS Binding Energy with Machine Learning: Domain Transfer and Data Limitations
- DOI
- 10.1021/acs.jcim.5c03121
- Published
- 2026-06-26
- 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.5c03121,
title = {Evaluating Molecular Representations for Predicting Cyclodextrin-PFAS Binding Energy with Machine Learning: Domain Transfer and Data Limitations},
author = {Cole Brzakala and Othonas A. Moultos and Jan Peter van der Hoek and Riccardo Taormina},
year = {2026},
journal = {Journal of Chemical Information and Modeling},
doi = {10.1021/acs.jcim.5c03121},
url = {https://doi.org/10.1021/acs.jcim.5c03121}
}RIS
TY - JOUR TI - Evaluating Molecular Representations for Predicting Cyclodextrin-PFAS Binding Energy with Machine Learning: Domain Transfer and Data Limitations AU - Cole Brzakala AU - Othonas A. Moultos AU - Jan Peter van der Hoek AU - Riccardo Taormina PY - 2026 JO - Journal of Chemical Information and Modeling DO - 10.1021/acs.jcim.5c03121 UR - https://doi.org/10.1021/acs.jcim.5c03121 ER -
APA
Brzakala, C., Moultos, O. A., Hoek, J. P. V. D., & Taormina, R. (2026). Evaluating Molecular Representations for Predicting Cyclodextrin-PFAS Binding Energy with Machine Learning: Domain Transfer and Data Limitations. Journal of Chemical Information and Modeling. https://doi.org/10.1021/acs.jcim.5c03121
Source records
- crossref · retrieved 2026-09-26T03:32:09.192Z