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Grégori Gerebtzoff

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Expert Opinion on Drug Metabolism & Toxicology|October 4, 2006
Enhancement of drug absorption by noncharged detergents through membrane and P-glycoprotein bindingAnna Seelig, Grégori Gerebtzoff
Journal of Chemical Information and Modeling|November 28, 2006
In silico prediction of blood-brain barrier permeation using the calculated molecular cross-sectional area as main parameterGrégori Gerebtzoff, Anna Seelig
Molecular Pharmaceutics|February 6, 2023
Systematic Evaluation of Local and Global Machine Learning Models for the Prediction of ADME PropertiesElena Di Lascio, Grégori Gerebtzoff, Raquel Rodríguez-Pérez
Chemical Research in Toxicology|March 19, 2024
Deep Learning Models Compared to Experimental Variability for the Prediction of CYP3A4 Time-Dependent InhibitionAndrin Fluetsch, Markus Trunzer, Grégori Gerebtzoff, et al.
Molecular Pharmaceutics|February 19, 2024
Adapting Deep Learning QSPR Models to Specific Drug Discovery ProjectsAndrin Fluetsch, Elena Di Lascio, Grégori Gerebtzoff, et al.
Chembiochem : a European Journal of Chemical Biology|May 4, 2004
Halogenation of drugs enhances membrane binding and permeationGrégori Gerebtzoff, Xiaochun Li-Blatter, Holger Fischer, et al.
Nature Communications|July 9, 2024
Application of machine learning models for property prediction to targeted protein degradersGiulia Peteani, Minh Tam Davide Huynh, Grégori Gerebtzoff, et al.
Molecular Pharmaceutics|November 6, 2024
DeepCt: Predicting Pharmacokinetic Concentration-Time Curves and Compartmental Models from Chemical Structure Using Deep LearningMaximilian Beckers, Dimitar Yonchev, Sandrine Desrayaud, et al.
Molecular Pharmaceutics|November 28, 2022
Multispecies Machine Learning Predictions of In Vitro Intrinsic Clearance with Uncertainty Quantification AnalysesRaquel Rodríguez-Pérez, Markus Trunzer, Nadine Schneider, et al.
Journal of Chemical Information and Modeling|June 23, 2022
Predicting In Vivo Compound Brain Penetration Using Multi-task Graph Neural NetworksSeid Hamzic, Richard Lewis, Sandrine Desrayaud, et al.
Pageof 2

Showing results (1-10 of 16) with videos related to

Sort By:
Pageof 2
Expert Opinion on Drug Metabolism & Toxicology|October 4, 2006
Enhancement of drug absorption by noncharged detergents through membrane and P-glycoprotein bindingAnna Seelig, Grégori Gerebtzoff
Journal of Chemical Information and Modeling|November 28, 2006
In silico prediction of blood-brain barrier permeation using the calculated molecular cross-sectional area as main parameterGrégori Gerebtzoff, Anna Seelig
Molecular Pharmaceutics|February 6, 2023
Systematic Evaluation of Local and Global Machine Learning Models for the Prediction of ADME PropertiesElena Di Lascio, Grégori Gerebtzoff, Raquel Rodríguez-Pérez
Chemical Research in Toxicology|March 19, 2024
Deep Learning Models Compared to Experimental Variability for the Prediction of CYP3A4 Time-Dependent InhibitionAndrin Fluetsch, Markus Trunzer, Grégori Gerebtzoff, et al.
Molecular Pharmaceutics|February 19, 2024
Adapting Deep Learning QSPR Models to Specific Drug Discovery ProjectsAndrin Fluetsch, Elena Di Lascio, Grégori Gerebtzoff, et al.
Chembiochem : a European Journal of Chemical Biology|May 4, 2004
Halogenation of drugs enhances membrane binding and permeationGrégori Gerebtzoff, Xiaochun Li-Blatter, Holger Fischer, et al.
Nature Communications|July 9, 2024
Application of machine learning models for property prediction to targeted protein degradersGiulia Peteani, Minh Tam Davide Huynh, Grégori Gerebtzoff, et al.
Molecular Pharmaceutics|November 6, 2024
DeepCt: Predicting Pharmacokinetic Concentration-Time Curves and Compartmental Models from Chemical Structure Using Deep LearningMaximilian Beckers, Dimitar Yonchev, Sandrine Desrayaud, et al.
Molecular Pharmaceutics|November 28, 2022
Multispecies Machine Learning Predictions of In Vitro Intrinsic Clearance with Uncertainty Quantification AnalysesRaquel Rodríguez-Pérez, Markus Trunzer, Nadine Schneider, et al.
Journal of Chemical Information and Modeling|June 23, 2022
Predicting In Vivo Compound Brain Penetration Using Multi-task Graph Neural NetworksSeid Hamzic, Richard Lewis, Sandrine Desrayaud, et al.
Pageof 2