Interpretable QSAR modelling for PPAR-γ agonist prediction by integrating a stacking strategy, docking, and MD simulations
- DOI
- 10.1007/s11030-026-11700-5
- Published
- 2026-08-28
- Container
- Molecular Diversity
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1007/s11030-026-11700-5,
title = {Interpretable QSAR modelling for PPAR-γ agonist prediction by integrating a stacking strategy, docking, and MD simulations},
author = {Phasit Charoenkwan and Ittipat Meewan and Nalini Schaduangrat and Watshara Shoombuatong},
year = {2026},
journal = {Molecular Diversity},
doi = {10.1007/s11030-026-11700-5},
url = {https://doi.org/10.1007/s11030-026-11700-5}
}RIS
TY - JOUR TI - Interpretable QSAR modelling for PPAR-γ agonist prediction by integrating a stacking strategy, docking, and MD simulations AU - Phasit Charoenkwan AU - Ittipat Meewan AU - Nalini Schaduangrat AU - Watshara Shoombuatong PY - 2026 JO - Molecular Diversity DO - 10.1007/s11030-026-11700-5 UR - https://doi.org/10.1007/s11030-026-11700-5 ER -
APA
Charoenkwan, P., Meewan, I., Schaduangrat, N., & Shoombuatong, W. (2026). Interpretable QSAR modelling for PPAR-γ agonist prediction by integrating a stacking strategy, docking, and MD simulations. Molecular Diversity. https://doi.org/10.1007/s11030-026-11700-5
Source records
- crossref · retrieved 2026-09-25T05:01:32.205Z