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Theoretical and Computational Chemistry

Working Paper

Direct Steering of de novo Molecular Generation using Descriptor Conditional Recurrent Neural Networks (cRNNs)

Panagiotis-Christos Kotsias, Josep Arús-Pous, Hongming Chen, Ola Engkvist, Christian Tyrchan, Esben Jannik Bjerrum

2,232

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2

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Theoretical and Computational Chemistry

Working Paper

Retrosynthetic Accessibility Score (RAscore) - Rapid Machine Learned Synthesizability Classification from AI Driven Retrosynthetic Planning

Amol Thakkar, Veronika Chadimova, Esben Jannik Bjerrum, Ola Engkvist, Jean-Louis Reymond

727

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2

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Theoretical and Computational Chemistry

Working Paper

Memory-Assisted Reinforcement Learning for Diverse Molecular De Novo Design

Thomas Blaschke, Ola Engkvist, Jürgen Bajorath, Hongming Chen

633

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1

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Theoretical and Computational Chemistry

Working Paper

Using Active Learning to Develop Machine Learning Models for Reaction Yield Prediction

Simon Viet Johansson, Hampus Gummesson Svensson, Esben Bjerrum, Alexander Schliep, Morteza Haghir Chehreghani, Christian Tyrchan, Ola Engkvist

614

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1

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Theoretical and Computational Chemistry

Working Paper

Levenshtein Augmentation Improves Performance of SMILES Based Deep-Learning Synthesis Prediction

Dean Sumner, Jiazhen He, Amol Thakkar, Ola Engkvist, Esben Jannik Bjerrum

787

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1

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Analytical Chemistry

Working Paper

Fast Prediction of Distances Between Synthetic Routes with Deep Learning

Samuel Genheden, Ola Engkvist, Esben Jannik Bjerrum

305

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Biological and Medicinal Chemistry

Working Paper

MELLODDY: cross pharma federated learning at unprecedented scale unlocks benefits in QSAR without compromising proprietary information

Wouter Heyndrickx, Lewis Mervin, Tobias Morawietz, Noé Sturm, Lukas Friedrich, Adam Zalewski, Anastasia Pentina, Lina Humbeck, Martijn Oldenhof, Ritsuya Niwayama, Peter Schmidtke, Nikolas Fechner, Jaak Simm, Adam Arany, Nicolas Drizard, Rama Jabal, Arina Afanasyeva, Regis Loeb, Shlok Verma, Simon Harnqvist, Matthew Holmes, Balasz Pejo, Maria Telenczuk, Nicholas Holway, Arne Dieckmann, Nicola Rieke, Friederike Zumsande, Djork-Arné Clevert, Michael Krug, Christopher Luscombe, Darren Green, Peter Ertl, Peter Antal, David Marcus, Nicolas Do Huu, Hideyoshi Fuji, Stephen Pickett, Gergely Acs, Eric Boniface, Bernd Beck, Yax Sun, Arnaud Gohier, Friedrich Rippmann, Ola Engkvist, Andreas H. Göller, Yves Moreau, Mathieu N. Galtier, Ansgar Schuffenhauer, Hugo Ceulemans

1,241

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Biological and Medicinal Chemistry

Working Paper

Collaborative Virtual Screening to Elaborate an Imidazo[1,2-A]pyridine Hit Series for Visceral Leishmaniasis

Benjamin Perry, yuichiro akao, Stacie Canan, Yafeng Cao, Kevin Condroski, Ola Engkvist, sachiko itono, rina kaki, chiaki kimura, Thierry Kogej, Charles E. Mowbray, kazuya nagaoka, Akira Naito, Hiromi Nakai, Garry Pairaudeau, Constantin Radu, Ieuan Roberts, mitsuyuki shimada, David Shum, Nao-aki Watanabe, huanxu xie, Shuji Yonezawa, Osamu Yoshida, Ryu Yoshida

332

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Theoretical and Computational Chemistry

Working Paper

De novo drug design using reinforcement learning with graph-based deep generative models

Sara Romeo Atance, Juan Viguera Diez, Ola Engkvist, Simon Olsson, Rocío Mercado

2,065

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3

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Theoretical and Computational Chemistry

Working Paper

Icolos: A workflow manager for structure based post-processing of de novo generated small molecules

J. Harry Moore, Matthias R. Bauer, Jeff Guo, Atanas Patronov, Ola Engkvist, Christian Margreitter

538

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46 results in Ola Engkvist in Authors: Ola Engkvist

Direct Steering of de novo Molecular Generation using Descriptor Conditional Recurrent Neural Networks (cRNNs)

Retrosynthetic Accessibility Score (RAscore) - Rapid Machine Learned Synthesizability Classification from AI Driven Retrosynthetic Planning

Memory-Assisted Reinforcement Learning for Diverse Molecular De Novo Design

Using Active Learning to Develop Machine Learning Models for Reaction Yield Prediction

Levenshtein Augmentation Improves Performance of SMILES Based Deep-Learning Synthesis Prediction

Fast Prediction of Distances Between Synthetic Routes with Deep Learning

MELLODDY: cross pharma federated learning at unprecedented scale unlocks benefits in QSAR without compromising proprietary information

Collaborative Virtual Screening to Elaborate an Imidazo[1,2-A]pyridine Hit Series for Visceral Leishmaniasis

De novo drug design using reinforcement learning with graph-based deep generative models

Icolos: A workflow manager for structure based post-processing of de novo generated small molecules

46 results in Authors: Ola Engkvist