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Feature importance of machine learning prediction models shows structurally active part and important physicochemical features in drug design

Katsunori Sasahara, Masakazu SHIBATA, Hiroyuki Sasabe, Tomoki Suzuki, Kenji Takeuchi, Ken Umehara, Eiji Kashiyama

2021Drug Metabolism and Pharmacokinetics17 citationsDOI

Topics & Concepts

Stability (learning theory)Machine learningArtificial intelligenceMetabolic stabilityComputer scienceQuantitative structure–activity relationshipBiological systemFeature (linguistics)Drug discoveryPredictive modellingProcess (computing)Active learning (machine learning)Biochemical engineeringChemistryEngineeringIn vitroBiologyBiochemistryOperating systemLinguisticsPhilosophyComputational Drug Discovery MethodsPharmacogenetics and Drug MetabolismAnalytical Chemistry and Chromatography
Feature importance of machine learning prediction models shows structurally active part and important physicochemical features in drug design | Litcius