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Ola Engkvist

Showing results (41-50 of 135) with videos related to

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Journal of Chemical Theory and Computation|April 20, 2026
Machine-Learned Electrostatic Potentials for Accurate Hydration Free Energy CalculationsMathias Hilfiker, Leonardo Medrano Sandonas, Alexandre Tkatchenko, et al.
Molecular Informatics|July 29, 2016
BIGCHEM: Challenges and Opportunities for Big Data Analysis in ChemistryIgor V Tetko, Ola Engkvist, Uwe Koch, et al.
Chemical Science|June 24, 2021
Retrosynthetic accessibility score (RAscore) - rapid machine learned synthesizability classification from AI driven retrosynthetic planningAmol Thakkar, Veronika Chadimová, Esben Jannik Bjerrum, et al.
Chemical Science|February 29, 2020
Datasets and their influence on the development of computer assisted synthesis planning tools in the pharmaceutical domainAmol Thakkar, Thierry Kogej, Jean-Louis Reymond, et al.
Angewandte Chemie (International Ed. in English)|January 29, 2014
Heart regeneration: opportunities and challenges for drug discovery with novel chemical and therapeutic methods or agentsAlleyn T Plowright, Ola Engkvist, Adrian Gill, et al.
Journal of Medicinal Chemistry|January 4, 2013
Systematic exploration of dual-acting modulators from a combined medicinal chemistry and biology perspectiveAurelie Bornot, Udo Bauer, Alastair Brown, et al.
Journal of Medicinal Chemistry|May 1, 2020
"Ring Breaker": Neural Network Driven Synthesis Prediction of the Ring System Chemical SpaceAmol Thakkar, Nidhal Selmi, Jean-Louis Reymond, et al.
Journal of Chemical Information and Modeling|October 11, 2022
<i>De Novo</i> Drug Design Using Reinforcement Learning with Graph-Based Deep Generative ModelsSara Romeo Atance, Juan Viguera Diez, Ola Engkvist, et al.
Drug Discovery Today|November 30, 2020
Uncertainty quantification in drug designLewis H Mervin, Simon Johansson, Elizaveta Semenova, et al.
Bioorganic & Medicinal Chemistry|July 19, 2021
De novo design with deep generative models based on 3D similarity scoringKostas Papadopoulos, Kathryn A Giblin, Jon Paul Janet, et al.
Pageof 14

Showing results (41-50 of 135) with videos related to

Sort By:
Pageof 14
Journal of Chemical Theory and Computation|April 20, 2026
Machine-Learned Electrostatic Potentials for Accurate Hydration Free Energy CalculationsMathias Hilfiker, Leonardo Medrano Sandonas, Alexandre Tkatchenko, et al.
Molecular Informatics|July 29, 2016
BIGCHEM: Challenges and Opportunities for Big Data Analysis in ChemistryIgor V Tetko, Ola Engkvist, Uwe Koch, et al.
Chemical Science|June 24, 2021
Retrosynthetic accessibility score (RAscore) - rapid machine learned synthesizability classification from AI driven retrosynthetic planningAmol Thakkar, Veronika Chadimová, Esben Jannik Bjerrum, et al.
Chemical Science|February 29, 2020
Datasets and their influence on the development of computer assisted synthesis planning tools in the pharmaceutical domainAmol Thakkar, Thierry Kogej, Jean-Louis Reymond, et al.
Angewandte Chemie (International Ed. in English)|January 29, 2014
Heart regeneration: opportunities and challenges for drug discovery with novel chemical and therapeutic methods or agentsAlleyn T Plowright, Ola Engkvist, Adrian Gill, et al.
Journal of Medicinal Chemistry|January 4, 2013
Systematic exploration of dual-acting modulators from a combined medicinal chemistry and biology perspectiveAurelie Bornot, Udo Bauer, Alastair Brown, et al.
Journal of Medicinal Chemistry|May 1, 2020
"Ring Breaker": Neural Network Driven Synthesis Prediction of the Ring System Chemical SpaceAmol Thakkar, Nidhal Selmi, Jean-Louis Reymond, et al.
Journal of Chemical Information and Modeling|October 11, 2022
<i>De Novo</i> Drug Design Using Reinforcement Learning with Graph-Based Deep Generative ModelsSara Romeo Atance, Juan Viguera Diez, Ola Engkvist, et al.
Drug Discovery Today|November 30, 2020
Uncertainty quantification in drug designLewis H Mervin, Simon Johansson, Elizaveta Semenova, et al.
Bioorganic & Medicinal Chemistry|July 19, 2021
De novo design with deep generative models based on 3D similarity scoringKostas Papadopoulos, Kathryn A Giblin, Jon Paul Janet, et al.
Pageof 14