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Dimitar Yonchev

Showing results (1-10 of 14) with videos related to

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Future Science OA|March 7, 2020
Integrating computational lead optimization diagnostics with analog design and candidate selectionDimitar Yonchev, Jürgen Bajorath
Future Science OA|September 28, 2020
Inhibitor bias in luciferase-based luminescence assaysDimitar Yonchev, Jürgen Bajorath
Journal of Computer-Aided Molecular Design|October 5, 2020
DeepCOMO: from structure-activity relationship diagnostics to generative molecular design using the compound optimization monitor methodologyDimitar Yonchev, Jürgen Bajorath
Future Science OA|May 28, 2021
Structured data sets of compounds with multi-target and corresponding single-target activity from biological assaysChristian Feldmann, Dimitar Yonchev, Jürgen Bajorath
Journal of Medicinal Chemistry|December 1, 2018
Computational Method to Evaluate Progress in Lead OptimizationMartin Vogt, Dimitar Yonchev, Jürgen Bajorath
Biomolecules|December 2, 2020
Analysis of Biological Screening Compounds with Single- or Multi-Target Activity via Diagnostic Machine LearningChristian Feldmann, Dimitar Yonchev, Jürgen Bajorath
Molecular Informatics|April 14, 2020
From SAR Diagnostics to Compound Design: Development Chronology of the Compound Optimization Monitor (COMO) MethodDimitar Yonchev, Martin Vogt, Jürgen Bajorath
Molecular Pharmaceutics|November 5, 2020
Systematic Data Analysis and Diagnostic Machine Learning Reveal Differences between Compounds with Single- and Multitarget ActivityChristian Feldmann, Dimitar Yonchev, Dagmar Stumpfe, et al.
Molecules (Basel, Switzerland)|November 23, 2019
Identifying Promiscuous Compounds with Activity against Different Target ClassesChristian Feldmann, Filip Miljković, Dimitar Yonchev, et al.
Nature Communications|July 19, 2023
A preclinical secondary pharmacology resource illuminates target-adverse drug reaction associations of marketed drugsJeffrey J Sutherland, Dimitar Yonchev, Alexander Fekete, et al.
Pageof 2

Showing results (1-10 of 14) with videos related to

Sort By:
Pageof 2
Future Science OA|March 7, 2020
Integrating computational lead optimization diagnostics with analog design and candidate selectionDimitar Yonchev, Jürgen Bajorath
Future Science OA|September 28, 2020
Inhibitor bias in luciferase-based luminescence assaysDimitar Yonchev, Jürgen Bajorath
Journal of Computer-Aided Molecular Design|October 5, 2020
DeepCOMO: from structure-activity relationship diagnostics to generative molecular design using the compound optimization monitor methodologyDimitar Yonchev, Jürgen Bajorath
Future Science OA|May 28, 2021
Structured data sets of compounds with multi-target and corresponding single-target activity from biological assaysChristian Feldmann, Dimitar Yonchev, Jürgen Bajorath
Journal of Medicinal Chemistry|December 1, 2018
Computational Method to Evaluate Progress in Lead OptimizationMartin Vogt, Dimitar Yonchev, Jürgen Bajorath
Biomolecules|December 2, 2020
Analysis of Biological Screening Compounds with Single- or Multi-Target Activity via Diagnostic Machine LearningChristian Feldmann, Dimitar Yonchev, Jürgen Bajorath
Molecular Informatics|April 14, 2020
From SAR Diagnostics to Compound Design: Development Chronology of the Compound Optimization Monitor (COMO) MethodDimitar Yonchev, Martin Vogt, Jürgen Bajorath
Molecular Pharmaceutics|November 5, 2020
Systematic Data Analysis and Diagnostic Machine Learning Reveal Differences between Compounds with Single- and Multitarget ActivityChristian Feldmann, Dimitar Yonchev, Dagmar Stumpfe, et al.
Molecules (Basel, Switzerland)|November 23, 2019
Identifying Promiscuous Compounds with Activity against Different Target ClassesChristian Feldmann, Filip Miljković, Dimitar Yonchev, et al.
Nature Communications|July 19, 2023
A preclinical secondary pharmacology resource illuminates target-adverse drug reaction associations of marketed drugsJeffrey J Sutherland, Dimitar Yonchev, Alexander Fekete, et al.
Pageof 2