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Martin Vogt

Showing results (21-30 of 87) with videos related to

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Journal of Chemical Information and Modeling|December 10, 2024
Influence of Data Curation and Confidence Levels on Compound Predictions Using Machine Learning ModelsElena Xerxa, Martin Vogt, Jürgen Bajorath
Journal of Computer-Aided Molecular Design|August 13, 2016
Maximum common substructure-based Tversky index: an asymmetric hybrid similarity measureRyo Kunimoto, Martin Vogt, Jürgen Bajorath
Chemistry (Weinheim an Der Bergstrasse, Germany)|September 21, 2004
Monosaccharides as silicon chelators: pentacoordinate bis(diolato)(phenyl)silicates with the cis-furanose isomers of common pentoses and hexosesPeter Klüfers, Florian Kopp, Martin Vogt
Future Science OA|October 2, 2018
Computationally derived compound profiling matricesMartin Vogt, Swarit Jasial, Jürgen Bajorath
Journal of Chemical Information and Modeling|January 22, 2010
Current trends in ligand-based virtual screening: molecular representations, data mining methods, new application areas, and performance evaluationHanna Geppert, Martin Vogt, Jürgen Bajorath
Journal of Chemical Information and Modeling|August 20, 2013
Searching for closely related ligands with different mechanisms of action using machine learning and mapping algorithmsJenny Balfer, Martin Vogt, Jürgen Bajorath
Journal of Medicinal Chemistry|December 1, 2018
Computational Method to Evaluate Progress in Lead OptimizationMartin Vogt, Dimitar Yonchev, Jürgen Bajorath
Journal of Computer-Aided Molecular Design|July 9, 2014
Design of an activity landscape view taking compound-based feature probabilities into accountBijun Zhang, Martin Vogt, Jürgen Bajorath
Journal of Cheminformatics|January 12, 2021
Activity landscape image analysis using convolutional neural networksJaved Iqbal, Martin Vogt, Jürgen Bajorath
Molecules (Basel, Switzerland)|September 3, 2020
Computational Method for Quantitative Comparison of Activity Landscapes on the Basis of Image DataJaved Iqbal, Martin Vogt, Jürgen Bajorath
Pageof 9

Showing results (21-30 of 87) with videos related to

Sort By:
Pageof 9
Journal of Chemical Information and Modeling|December 10, 2024
Influence of Data Curation and Confidence Levels on Compound Predictions Using Machine Learning ModelsElena Xerxa, Martin Vogt, Jürgen Bajorath
Journal of Computer-Aided Molecular Design|August 13, 2016
Maximum common substructure-based Tversky index: an asymmetric hybrid similarity measureRyo Kunimoto, Martin Vogt, Jürgen Bajorath
Chemistry (Weinheim an Der Bergstrasse, Germany)|September 21, 2004
Monosaccharides as silicon chelators: pentacoordinate bis(diolato)(phenyl)silicates with the cis-furanose isomers of common pentoses and hexosesPeter Klüfers, Florian Kopp, Martin Vogt
Future Science OA|October 2, 2018
Computationally derived compound profiling matricesMartin Vogt, Swarit Jasial, Jürgen Bajorath
Journal of Chemical Information and Modeling|January 22, 2010
Current trends in ligand-based virtual screening: molecular representations, data mining methods, new application areas, and performance evaluationHanna Geppert, Martin Vogt, Jürgen Bajorath
Journal of Chemical Information and Modeling|August 20, 2013
Searching for closely related ligands with different mechanisms of action using machine learning and mapping algorithmsJenny Balfer, Martin Vogt, Jürgen Bajorath
Journal of Medicinal Chemistry|December 1, 2018
Computational Method to Evaluate Progress in Lead OptimizationMartin Vogt, Dimitar Yonchev, Jürgen Bajorath
Journal of Computer-Aided Molecular Design|July 9, 2014
Design of an activity landscape view taking compound-based feature probabilities into accountBijun Zhang, Martin Vogt, Jürgen Bajorath
Journal of Cheminformatics|January 12, 2021
Activity landscape image analysis using convolutional neural networksJaved Iqbal, Martin Vogt, Jürgen Bajorath
Molecules (Basel, Switzerland)|September 3, 2020
Computational Method for Quantitative Comparison of Activity Landscapes on the Basis of Image DataJaved Iqbal, Martin Vogt, Jürgen Bajorath
Pageof 9