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Désiré Meledje

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Open access Aug 2026

MACHINE LEARNING-BASED QSAR MODELING OF TRICLOSAN ANALOGS FOR ANTIPLASMODIAL ACTIVITY PREDICTION USING SHRINKAGE REGRESSION MODEL AND TOPOLOGICAL-PHYSICOCHEMICAL DESCRIPTORS

Drug-resistant Plasmodium falciparum continues to threaten malaria control, necessitating new antimalarial discovery strategies. QSAR modeling with machine learning offers a cost-effective approach to relate molecular features to biological activity and prioritize candidate compounds for further development. In particu...

Désiré Meledje, Aubin N’GUESSAN, Kady Silué et al. · 0 citations

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