Development of an interpretable QSPR model to predict the octanol-water partition coefficient based on three artificial intelligence algorithms

Development of an interpretable QSPR model to predict the octanol-water partition coefficient based on three artificial intelligence algorithms

This study aims to significantly improve existing quantitative structure-property relationship (QSPR) models for predicting the octanol-water partition coefficient (KOW). This is because accurate predictions of KOW are crucial for assessing the environmental behavior and bioaccumulation potential of...

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Manylion Llyfryddiaeth
Prif Awduron: Ao Yang, Shirui Sun, Lu Qi, Zong Yang Kong, Jaka Sunarso, Weifeng Shen
Fformat: Erthygl
Iaith:English
Cyhoeddwyd: KeAi Communications Co. Ltd. 2025-06-01
Cyfres:Green Chemical Engineering
Pynciau:
Octanol-water partition coefficient
Environmental property
QSPR
Interpretable model
Machine learning
Mynediad Ar-lein:http://www.sciencedirect.com/science/article/pii/S2666952824000542

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http://www.sciencedirect.com/science/article/pii/S2666952824000542

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