Ola Engkvist - RankMe

107 papers A* 3B 2Journal 90Unranked 12

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Achieving well-informed decision-making in drug discovery: a comprehensive calibration study using neural network-based structure-activity models. J. Cheminformatics Hannah Rosa Friesacher, Ola Engkvist, Lewis H. Mervin, Yves Moreau, Adam Arany
2025	A*	`conf`	Boltzmann priors for Implicit Transfer Operators. ICLR Juan Viguera Diez, Mathias Jacob Schreiner, Ola Engkvist, Simon Olsson
2025	J	`jnl`	Diverse Mini-Batch Selection in Reinforcement Learning for Efficient Chemical Exploration in de novo Drug Design. CoRR Hampus Gummesson Svensson, Ola Engkvist, Jon Paul Janet, Christian Tyrchan, Morteza Haghir Chehreghani
2025	A*	`conf`	Diversity-Aware Reinforcement Learning for de novo Drug Design. IJCAI Hampus Gummesson Svensson, Christian Tyrchan, Ola Engkvist, Morteza Haghir Chehreghani
2025	J	`jnl`	E-GuARD: expert-guided augmentation for the robust detection of compounds interfering with biological assays. J. Cheminformatics Vincenzo Palmacci, Yasmine Nahal, Matthias Welsch, Ola Engkvist, Samuel Kaski, Johannes Kirchmair
2025	J	`jnl`	Exploring Modularity of Agentic Systems for Drug Discovery. CoRR Laura van Weesep, Samuel Genheden, Ola Engkvist, Jens Sjölund
2025	J	`jnl`	FlexiFlow: decomposable flow matching for generation of flexible molecular ensemble. CoRR Riccardo Tedoldi, Ola Engkvist, Patrick Bryant, Hossein Azizpour, Jon Paul Janet, Alessandro Tibo
2025	—	`conf`	MolEncoder: Improved Masked Language Modeling for Molecules. ICANN (5) Fabian Krüger, Nicklas Österbacka, Mikhail Kabeshov, Ola Engkvist, Igor V. Tetko
2025	J	`jnl`	Practically Significant Method Comparison Protocols for Machine Learning in Small Molecule Drug Discovery. J. Chem. Inf. Model. Jeremy R. Ash, Cas Wognum, Raquel Rodríguez-Pérez, Matteo Aldeghi, Alan C. Cheng, Djork-Arné Clevert, Ola Engkvist, Cheng Fang, Daniel J. Price, Jacqueline M. Hughes-Oliver, W. Patrick Walters
2025	J	`jnl`	Publishing neural networks in drug discovery might compromise training data privacy. J. Cheminformatics Fabian Krüger, Johan Östman, Lewis H. Mervin, Igor V. Tetko, Ola Engkvist
2025	J	`jnl`	Temporal Distribution Shift in Real-World Pharmaceutical Data: Implications for Uncertainty Quantification in QSAR Models. CoRR Hannah Rosa Friesacher, Emma Svensson, Susanne Winiwarter, Lewis H. Mervin, Adam Arany, Ola Engkvist
2025	J	`jnl`	WEISS: Wasserstein efficient sampling strategy for LLMs in drug design. Mach. Learn. Sci. Technol. Riccardo Tedoldi, Junyong Li, Ola Engkvist, Andrea Passerini, Annie M. Westerlund, Alessandro Tibo
2024	J	`jnl`	A call for an industry-led initiative to critically assess machine learning for real-world drug discovery. Nat. Mac. Intell. Cas Wognum, Jeremy R. Ash, Matteo Aldeghi, Raquel Rodríguez-Pérez, Cheng Fang, Alan C. Cheng, Daniel J. Price, Djork-Arné Clevert, Ola Engkvist, W. Patrick Walters
2024	J	`jnl`	Achieving Well-Informed Decision-Making in Drug Discovery: A Comprehensive Calibration Study using Neural Network-Based Structure-Activity Models. CoRR Hannah Rosa Friesacher, Ola Engkvist, Lewis H. Mervin, Yves Moreau, Adam Arany
2024	J	`jnl`	AiZynthFinder 4.0: developments based on learnings from 3 years of industrial application. J. Cheminformatics Lakshidaa Saigiridharan, Alan Kai Hassen, Helen Lai, Paula Torren-Peraire, Ola Engkvist, Samuel Genheden
2024	J	`jnl`	Diversity-Aware Reinforcement Learning for de novo Drug Design. CoRR Hampus Gummesson Svensson, Christian Tyrchan, Ola Engkvist, Morteza Haghir Chehreghani
2024	J	`jnl`	Enhancing Uncertainty Quantification in Drug Discovery with Censored Regression Labels. CoRR Emma Svensson, Hannah Rosa Friesacher, Susanne Winiwarter, Lewis H. Mervin, Adam Arany, Ola Engkvist
2024	J	`jnl`	Evaluation of reinforcement learning in transformer-based molecular design. J. Cheminformatics Jiazhen He, Alessandro Tibo, Jon Paul Janet, Eva Nittinger, Christian Tyrchan, Werngard Czechtizky, Ola Engkvist
2024	J	`jnl`	Generation of conformational ensembles of small molecules via surrogate model-assisted molecular dynamics. Mach. Learn. Sci. Technol. Juan Viguera Diez, Sara Romeo Atance, Ola Engkvist, Simon Olsson
2024	J	`jnl`	Human-in-the-loop active learning for goal-oriented molecule generation. J. Cheminformatics Yasmine Nahal, Janosch Menke, Julien Martinelli, Markus Heinonen, Mikhail Kabeshov, Jon Paul Janet, Eva Nittinger, Ola Engkvist, Samuel Kaski
2024	—	`conf`	Leveraging Quantum Mechanical Properties to Predict Solvent Effects on Large Drug-Like Molecules. AIDD@ICANN Mathias Hilfiker, Leonardo Medrano Sandonas, Marco Klähn, Ola Engkvist, Alexandre Tkatchenko
2024	J	`jnl`	MELLODDY: Cross-pharma Federated Learning at Unprecedented Scale Unlocks Benefits in QSAR without Compromising Proprietary Information. J. Chem. Inf. Model. Wouter Heyndrickx, Lewis H. 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, Balazs Pejo, Maria Telenczuk, Nicholas Holway, Arne Dieckmann, Nicola Rieke, Friederike Zumsande, Djork-Arné Clevert, Michael Krug, Christopher N. Luscombe, Darren V. S. Green, Peter Ertl, Peter Antal, David Marcus, Nicolas Do Huu, Hideyoshi Fuji, Stephen D. Pickett, Gergely Ács, Eric Boniface, Bernd Beck, Yax Sun, Arnaud Gohier, Friedrich Rippmann, Ola Engkvist, Andreas H. Göller, Yves Moreau, Mathieu N. Galtier, Ansgar Schuffenhauer, Hugo Ceulemans
2024	J	`jnl`	Metis: a python-based user interface to collect expert feedback for generative chemistry models. J. Cheminformatics Janosch Menke, Yasmine Nahal, Esben Jannik Bjerrum, Mikhail Kabeshov, Samuel Kaski, Ola Engkvist
2024	J	`jnl`	Navigating the Maize: Cyclic and conditional computational graphs for molecular simulation. CoRR Thomas Löhr, Michael Dodds, Lili Cao, Mikhail Kabeshov, Michele Assante, Jon Paul Janet, Marco Klähn, Ola Engkvist
2024	J	`jnl`	PepINVENT: Generative peptide design beyond the natural amino acids. CoRR Gökçe Geylan, Jon Paul Janet, Alessandro Tibo, Jiazhen He, Atanas Patronov, Mikhail Kabeshov, Florian David, Werngard Czechtizky, Ola Engkvist, Leonardo De Maria
2024	J	`jnl`	Publishing Neural Networks in Drug Discovery Might Compromise Training Data Privacy. CoRR Fabian Krüger, Johan Östman, Lewis H. Mervin, Igor V. Tetko, Ola Engkvist
2024	J	`jnl`	QSARtuna: An Automated QSAR Modeling Platform for Molecular Property Prediction in Drug Design. J. Chem. Inf. Model. Lewis H. Mervin, Alexey Voronov, Mikhail Kabeshov, Ola Engkvist
2024	—	`conf`	Registries in Machine Learning-Based Drug Discovery: A Shortcut to Code Reuse. AIDD@ICANN Peter B. R. Hartog, Emma Svensson, Lewis H. Mervin, Samuel Genheden, Ola Engkvist, Igor V. Tetko
2024	J	`jnl`	Reinvent 4: Modern AI-driven generative molecule design. J. Cheminformatics Hannes H. Loeffler, Jiazhen He, Alessandro Tibo, Jon Paul Janet, Alexey Voronov, Lewis H. Mervin, Ola Engkvist
2024	—	`conf`	Temporal Evaluation of Probability Calibration with Experimental Errors. AIDD@ICANN Hannah Rosa Friesacher, Emma Svensson, Adam Arany, Lewis H. Mervin, Ola Engkvist
2024	—	`conf`	Temporal Evaluation of Uncertainty Quantification Under Distribution Shift. AIDD@ICANN Emma Svensson, Hannah Rosa Friesacher, Adam Arany, Lewis H. Mervin, Ola Engkvist
2024	—	`conf`	Towards Interpretable Models of Chemist Preferences for Human-in-the-Loop Assisted Drug Discovery. AIDD@ICANN Yasmine Nahal, Markus Heinonen, Mikhail Kabeshov, Jon Paul Janet, Eva Nittinger, Ola Engkvist, Samuel Kaski
2024	J	`jnl`	Utilizing reinforcement learning for de novo drug design. Mach. Learn. Hampus Gummesson Svensson, Christian Tyrchan, Ola Engkvist, Morteza Haghir Chehreghani
2023	J	`jnl`	AiZynthTrain: Robust, Reproducible, and Extensible Pipelines for Training Synthesis Prediction Models. J. Chem. Inf. Model. Samuel Genheden, Per-Ola Norrby, Ola Engkvist
2023	J	`jnl`	Blinded Predictions and Post Hoc Analysis of the Second Solubility Challenge Data: Exploring Training Data and Feature Set Selection for Machine and Deep Learning Models. J. Chem. Inf. Model. Jonathan G. M. Conn, James W. Carter, Justin J. A. Conn, Vigneshwari Subramanian, Andrew Baxter, Ola Engkvist, Antonio Llinàs, Ekaterina Ratkova, Stephen D. Pickett, James L. McDonagh, David S. Palmer
2023	B	`conf`	Diverse Data Expansion with Semi-Supervised k-Determinantal Point Processes. IEEE Big Data Simon Johansson, Ola Engkvist, Morteza Haghir Chehreghani, Alexander Schliep
2023	A*	`conf`	Industry-Scale Orchestrated Federated Learning for Drug Discovery. AAAI Martijn Oldenhof, Gergely Ács, Balázs Pejó, Ansgar Schuffenhauer, Nicholas Holway, Noé Sturm, Arne Dieckmann, Oliver Fortmeier, Eric Boniface, Clément Mayer, Arnaud Gohier, Peter Schmidtke, Ritsuya Niwayama, Dieter Kopecky, Lewis H. Mervin, Prakash Chandra Rathi, Lukas Friedrich, András Formanek, Peter Antal, Jordon Rahaman, Adam Zalewski, Wouter Heyndrickx, Ezron Oluoch, Manuel Stößel, Michal Vanco, David Endico, Fabien Gelus, Thaïs de Boisfossé, Adrien Darbier, Ashley Nicollet, Matthieu Blottière, Maria Telenczuk, Van Tien Nguyen, Thibaud Martinez, Camille Boillet, Kelvin Moutet, Alexandre Picosson, Aurélien Gasser, Inal Djafar, Antoine Simon, Adam Arany, Jaak Simm, Yves Moreau, Ola Engkvist, Hugo Ceulemans, Camille Marini, Mathieu Galtier
2023	J	`jnl`	Utilizing Reinforcement Learning for de novo Drug Design. CoRR Hampus Gummesson Svensson, Christian Tyrchan, Ola Engkvist, Morteza Haghir Chehreghani
2022	J	`jnl`	A review of biomedical datasets relating to drug discovery: a knowledge graph perspective. Briefings Bioinform. Stephen Bonner, Ian P. Barrett, Cheng Ye, Rowan Swiers, Ola Engkvist, Andreas Bender, Charles Tapley Hoyt, William L. Hamilton
2022	J	`jnl`	Author Correction: Improving de novo molecular design with curriculum learning. Nat. Mach. Intell. Jeff Guo, Vendy Fialková, Juan Diego Arango, Christian Margreitter, Jon Paul Janet, Kostas Papadopoulos, Ola Engkvist, Atanas Patronov
2022	B	`conf`	Autonomous Drug Design with Multi-Armed Bandits. IEEE Big Data Hampus Gummesson Svensson, Esben Jannik Bjerrum, Christian Tyrchan, Ola Engkvist, Morteza Haghir Chehreghani
2022	J	`jnl`	Autonomous Drug Design with Multi-armed Bandits. CoRR Hampus Gummesson Svensson, Esben Jannik Bjerrum, Christian Tyrchan, Ola Engkvist, Morteza Haghir Chehreghani
2022	J	`jnl`	Exploring Graph Traversal Algorithms in Graph-Based Molecular Generation. J. Chem. Inf. Model. Rocío Mercado, Esben Jannik Bjerrum, Ola Engkvist
2022	J	`jnl`	Fast prediction of distances between synthetic routes with deep learning. Mach. Learn. Sci. Technol. Samuel Genheden, Ola Engkvist, Esben Jannik Bjerrum
2022	J	`jnl`	Human-in-the-loop assisted de novo molecular design. J. Cheminformatics Iiris Sundin, Alexey Voronov, Haoping Xiao, Kostas Papadopoulos, Esben Jannik Bjerrum, Markus Heinonen, Atanas Patronov, Samuel Kaski, Ola Engkvist
2022	J	`jnl`	Icolos: a workflow manager for structure-based post-processing of Bioinform. James Harry Moore, Matthias R. Bauer, Jeff Guo, Atanas Patronov, Ola Engkvist, Christian Margreitter
2022	J	`jnl`	Implications of topological imbalance for representation learning on biomedical knowledge graphs. Briefings Bioinform. Stephen Bonner, Ufuk Kirik, Ola Engkvist, Jian Tang, Ian P. Barrett
2022	J	`jnl`	Improving de novo molecular design with curriculum learning. Nat. Mach. Intell. Jeff Guo, Vendy Fialková, Juan Diego Arango, Christian Margreitter, Jon Paul Janet, Kostas Papadopoulos, Ola Engkvist, Atanas Patronov
2022	J	`jnl`	Industry-Scale Orchestrated Federated Learning for Drug Discovery. CoRR Martijn Oldenhof, Gergely Ács, Balázs Pejó, Ansgar Schuffenhauer, Nicholas Holway, Noé Sturm, Arne Dieckmann, Oliver Fortmeier, Eric Boniface, Clément Mayer, Arnaud Gohier, Peter Schmidtke, Ritsuya Niwayama, Dieter Kopecky, Lewis H. Mervin, Prakash Chandra Rathi, Lukas Friedrich, András Formanek, Peter Antal, Jordon Rahaman, Adam Zalewski, Ezron Oluoch, Manuel Stößel, Michal Vanco, David Endico, Fabien Gelus, Thaïs de Boisfossé, Adrien Darbier, Ashley Nicollet, Matthieu Blottière, Maria Telenczuk, Van Tien Nguyen, Thibaud Martinez, Camille Boillet, Kelvin Moutet, Alexandre Picosson, Aurélien Gasser, Inal Djafar, Adam Arany, Jaak Simm, Yves Moreau, Ola Engkvist, Hugo Ceulemans, Camille Marini, Mathieu Galtier
2022	J	`jnl`	LibINVENT: Reaction-based Generative Scaffold Decoration for J. Chem. Inf. Model. Vendy Fialková, Jiaxi Zhao, Kostas Papadopoulos, Ola Engkvist, Esben Jannik Bjerrum, Thierry Kogej, Atanas Patronov
2022	J	`jnl`	Transformer-based molecular optimization beyond matched molecular pairs. J. Cheminformatics Jiazhen He, Eva Nittinger, Christian Tyrchan, Werngard Czechtizky, Atanas Patronov, Esben Jannik Bjerrum, Ola Engkvist
2021	J	`jnl`	A Review of Biomedical Datasets Relating to Drug Discovery: A Knowledge Graph Perspective. CoRR Stephen Bonner, Ian P. Barrett, Cheng Ye, Rowan Swiers, Ola Engkvist, Andreas Bender, William L. Hamilton
2021	J	`jnl`	Artificial applicability labels for improving policies in retrosynthesis prediction. Mach. Learn. Sci. Technol. Esben Jannik Bjerrum, Amol Thakkar, Ola Engkvist
2021	J	`jnl`	Clustering of Synthetic Routes Using Tree Edit Distance. J. Chem. Inf. Model. Samuel Genheden, Ola Engkvist, Esben Jannik Bjerrum
2021	J	`jnl`	Comparative Study of Deep Generative Models on Chemical Space Coverage. J. Chem. Inf. Model. Jie Zhang, Rocío Mercado, Ola Engkvist, Hongming Chen
2021	J	`jnl`	Comparison of Chemical Structure and Cell Morphology Information for Multitask Bioactivity Predictions. J. Chem. Inf. Model. Maria-Anna Trapotsi, Lewis H. Mervin, Avid M. Afzal, Noé Sturm, Ola Engkvist, Ian P. Barrett, Andreas Bender
2021	J	`jnl`	DockStream: a docking wrapper to enhance de novo molecular design. J. Cheminformatics Jeff Guo, Jon Paul Janet, Matthias R. Bauer, Eva Nittinger, Kathryn A. Giblin, Kostas Papadopoulos, Alexey Voronov, Atanas Patronov, Ola Engkvist, Christian Margreitter
2021	J	`jnl`	Graph networks for molecular design. Mach. Learn. Sci. Technol. Rocío Mercado, Tobias Rastemo, Edvard Lindelöf, Günter Klambauer, Ola Engkvist, Hongming Chen, Esben Jannik Bjerrum
2021	J	`jnl`	Implications of Topological Imbalance for Representation Learning on Biomedical Knowledge Graphs. CoRR Stephen Bonner, Ufuk Kirik, Ola Engkvist, Jian Tang, Ian P. Barrett
2021	J	`jnl`	MAIP: a web service for predicting blood-stage malaria inhibitors. J. Cheminformatics Nicolas Bosc, Eloy Felix, Ricardo Arcila, David Mendez, Martin R. Saunders, Darren V. S. Green, Jason Ochoada, Anang A. Shelat, Eric J. Martin, Preeti Iyer, Ola Engkvist, Andreas Verras, James Duffy, Jeremy N. Burrows, J. Mark F. Gardner, Andrew R. Leach
2021	J	`jnl`	Molecular optimization by capturing chemist's intuition using deep neural networks. J. Cheminformatics Jiazhen He, Huifang You, Emil Sandström, Eva Nittinger, Esben Jannik Bjerrum, Christian Tyrchan, Werngard Czechtizky, Ola Engkvist
2021	—	`conf`	Parallel Capsule Networks for Classification of White Blood Cells. MICCAI (7) Juan P. Vigueras-Guillén, Arijit Patra, Ola Engkvist, Frank Seeliger
2021	J	`jnl`	Parallel Capsule Networks for Classification of White Blood Cells. CoRR Juan P. Vigueras-Guillén, Arijit Patra, Ola Engkvist, Frank Seeliger
2021	J	`jnl`	Probabilistic Random Forest improves bioactivity predictions close to the classification threshold by taking into account experimental uncertainty. J. Cheminformatics Lewis H. Mervin, Maria-Anna Trapotsi, Avid M. Afzal, Ian P. Barrett, Andreas Bender, Ola Engkvist
2021	J	`jnl`	Understanding the Performance of Knowledge Graph Embeddings in Drug Discovery. CoRR Stephen Bonner, Ian P. Barrett, Cheng Ye, Rowan Swiers, Ola Engkvist, William L. Hamilton
2020	J	`jnl`	AiZynthFinder: a fast, robust and flexible open-source software for retrosynthetic planning. J. Cheminformatics Samuel Genheden, Amol Thakkar, Veronika Chadimová, Jean-Louis Reymond, Ola Engkvist, Esben Jannik Bjerrum
2020	J	`jnl`	Building attention and edge message passing neural networks for bioactivity and physical-chemical property prediction. J. Cheminformatics Michael Withnall, Edvard Lindelöf, Ola Engkvist, Hongming Chen
2020	J	`jnl`	Comparison of Scaling Methods to Obtain Calibrated Probabilities of Activity for Protein-Ligand Predictions. J. Chem. Inf. Model. Lewis H. Mervin, Avid M. Afzal, Ola Engkvist, Andreas Bender
2020	J	`jnl`	Direct steering of de novo molecular generation with descriptor conditional recurrent neural networks. Nat. Mach. Intell. Panagiotis-Christos Kotsias, Josep Arús-Pous, Hongming Chen, Ola Engkvist, Christian Tyrchan, Esben Jannik Bjerrum
2020	J	`jnl`	From Big Data to Artificial Intelligence: chemoinformatics meets new challenges. J. Cheminformatics Igor V. Tetko, Ola Engkvist
2020	J	`jnl`	Industry-scale application and evaluation of deep learning for drug target prediction. J. Cheminformatics Noé Sturm, Andreas Mayr, Thanh Le Van, Vladimir I. Chupakhin, Hugo Ceulemans, Jörg K. Wegner, José Felipe Golib Dzib, Nina Jeliazkova, Yves Vandriessche, Stanislav Böhm, Vojtech Cima, Jan Martinovic, Nigel Greene, Tom Vander Aa, Thomas J. Ashby, Sepp Hochreiter, Ola Engkvist, Günter Klambauer, Hongming Chen
2020	J	`jnl`	Molecular representations in AI-driven drug discovery: a review and practical guide. J. Cheminformatics Laurianne David, Amol Thakkar, Rocío Mercado, Ola Engkvist
2020	J	`jnl`	Multisolvent Models for Solvation Free Energy Predictions Using 3D-RISM Hydration Thermodynamic Descriptors. J. Chem. Inf. Model. Vigneshwari Subramanian, Ekaterina Ratkova, David Palmer, Ola Engkvist, Maxim V. Fedorov, Antonio Llinàs
2020	J	`jnl`	REINVENT 2.0: An AI Tool for De Novo Drug Design. J. Chem. Inf. Model. Thomas Blaschke, Josep Arús-Pous, Hongming Chen, Christian Margreitter, Christian Tyrchan, Ola Engkvist, Kostas Papadopoulos, Atanas Patronov
2020	J	`jnl`	SMILES-based deep generative scaffold decorator for de-novo drug design. J. Cheminformatics Josep Arús-Pous, Atanas Patronov, Esben Jannik Bjerrum, Christian Tyrchan, Jean-Louis Reymond, Hongming Chen, Ola Engkvist
2019	J	`jnl`	A de novo molecular generation method using latent vector based generative adversarial network. J. Cheminformatics Oleksii Prykhodko, Simon Johansson, Panagiotis-Christos Kotsias, Josep Arús-Pous, Esben Jannik Bjerrum, Ola Engkvist, Hongming Chen
2019	J	`jnl`	Accurate Hit Estimation for Iterative Screening Using Venn-ABERS Predictors. J. Chem. Inf. Model. Rubén Buendía, Thierry Kogej, Ola Engkvist, Lars Carlsson, Henrik Linusson, Ulf Johansson, Paolo Toccaceli, Ernst Ahlberg
2019	J	`jnl`	Application of Bioactivity Profile-Based Fingerprints for Building Machine Learning Models. J. Chem. Inf. Model. Noé Sturm, Jiangming Sun, Yves Vandriessche, Andreas Mayr, Günter Klambauer, Lars Carlsson, Ola Engkvist, Hongming Chen
2019	—	`conf`	Attention and Edge Memory Convolution for Bioactivity Prediction. ICANN (Workshop) Michael Withnall, Edvard Lindelöf, Ola Engkvist, Hongming Chen
2019	J	`jnl`	Combining structural and bioactivity-based fingerprints improves prediction performance and scaffold hopping capability. J. Cheminformatics Oliver Laufkötter, Noé Sturm, Jürgen Bajorath, Hongming Chen, Ola Engkvist
2019	J	`jnl`	Exploring the GDB-13 chemical space using deep generative models. J. Cheminformatics Josep Arús-Pous, Thomas Blaschke, Silas Ulander, Jean-Louis Reymond, Hongming Chen, Ola Engkvist
2019	—	`conf`	Improving Deep Generative Models with Randomized SMILES. ICANN (Workshop) Josep Arús-Pous, Simon Johansson, Oleksii Prykhodko, Esben Jannik Bjerrum, Christian Tyrchan, Jean-Louis Reymond, Hongming Chen, Ola Engkvist
2019	—	`conf`	Neural Network Guided Tree-Search Policies for Synthesis Planning. ICANN (Workshop) Amol Thakkar, Esben Jannik Bjerrum, Ola Engkvist, Jean-Louis Reymond
2019	J	`jnl`	Randomized SMILES strings improve the quality of molecular generative models. J. Cheminformatics Josep Arús-Pous, Simon Johansson, Oleksii Prykhodko, Esben Jannik Bjerrum, Christian Tyrchan, Jean-Louis Reymond, Hongming Chen, Ola Engkvist
2018	J	`jnl`	Orthologue chemical space and its influence on target prediction. Bioinform. Lewis H. Mervin, Krishna C. Bulusu, Leen Kalash, Avid M. Afzal, Fredrik Svensson, Mike A. Firth, Ian P. Barrett, Ola Engkvist, Andreas Bender
2018	—	`conf`	Venn-Abers predictors for improved compound iterative screening in drug discovery. COPA Rubén Buendía, Ola Engkvist, Lars Carlsson, Thierry Kogej, Ernst Ahlberg
2017	J	`jnl`	Application of generative autoencoder in de novo molecular design. CoRR Thomas Blaschke, Marcus Olivecrona, Ola Engkvist, Jürgen Bajorath, Hongming Chen
2017	J	`jnl`	Applying Mondrian Cross-Conformal Prediction To Estimate Prediction Confidence on Large Imbalanced Bioactivity Data Sets. J. Chem. Inf. Model. Jiangming Sun, Lars Carlsson, Ernst Ahlberg, Ulf Norinder, Ola Engkvist, Hongming Chen
2017	J	`jnl`	Erratum to: ExCAPE-DB: an integrated large scale dataset facilitating Big Data analysis in chemogenomics. J. Cheminformatics Jiangming Sun, Nina Jeliazkova, Vladimir I. Chupakhin, José Felipe Golib Dzib, Ola Engkvist, Lars Carlsson, Jörg K. Wegner, Hugo Ceulemans, Ivan Georgiev, Vedrin Jeliazkov, Nikolay T. Kochev, Thomas J. Ashby, Hongming Chen
2017	J	`jnl`	ExCAPE-DB: an integrated large scale dataset facilitating Big Data analysis in chemogenomics. J. Cheminformatics Jiangming Sun, Nina Jeliazkova, Vladimir I. Chupakhin, José Felipe Golib Dzib, Ola Engkvist, Lars Carlsson, Jörg K. Wegner, Hugo Ceulemans, Ivan Georgiev, Vedrin Jeliazkov, Nikolay T. Kochev, Thomas J. Ashby, Hongming Chen
2017	J	`jnl`	Innovation in Small-Molecule-Druggable Chemical Space: Where are the Initial Modulators of New Targets Published? J. Chem. Inf. Model. Stephanie K. Ashenden, Thierry Kogej, Ola Engkvist, Andreas Bender
2017	J	`jnl`	Molecular De Novo Design through Deep Reinforcement Learning. CoRR Marcus Olivecrona, Thomas Blaschke, Ola Engkvist, Hongming Chen
2017	J	`jnl`	Molecular de-novo design through deep reinforcement learning. J. Cheminformatics Marcus Olivecrona, Thomas Blaschke, Ola Engkvist, Hongming Chen
2017	—	`conf`	Using Conformal Prediction to Prioritize Compound Synthesis in Drug Discovery. COPA Ernst Ahlberg, Susanne Winiwarter, Henrik Boström, Henrik Linusson, Tuve Löfström, Ulf Norinder, Ulf Johansson, Ola Engkvist, Oscar Hammar, Claus Bendtsen, Lars Carlsson
2015	J	`jnl`	Investigating Pharmacological Similarity by Charting Chemical Space. J. Chem. Inf. Model. Rosa Buonfiglio, Ola Engkvist, Péter L. Várkonyi, Astrid Henz, Elisabet Vikeved, Anders Backlund, Thierry Kogej
2015	J	`jnl`	Target prediction utilising negative bioactivity data covering large chemical space. J. Cheminformatics Lewis H. Mervin, Avid M. Afzal, Georgios Drakakis, Richard Lewis, Ola Engkvist, Andreas Bender
2014	J	`jnl`	HTS explorer. J. Cheminformatics Christoph Müller, Isabella Feierberg, Ola Engkvist, Christian Tyrchan
2014	J	`jnl`	Hit series selection in noisy HTS data: clustering techniques, statistical tests and data visualisations. J. Cheminformatics Christoph Müller, Daniel L. Ormsby, Isabella Feierberg, Ola Engkvist, Christian Tyrchan, Michael J. Hartshorn
2014	J	`jnl`	Ligand-Based Target Prediction with Signature Fingerprints. J. Chem. Inf. Model. Jonathan Alvarsson, Martin Eklund, Ola Engkvist, Ola Spjuth, Lars Carlsson, Jarl E. S. Wikberg, Tobias Noeske
2010	J	`jnl`	Molecular Topology Analysis of the Differences between Drugs, Clinical Candidate Compounds, and Bioactive Molecules. J. Chem. Inf. Model. Hongming Chen, Yidong Yang, Ola Engkvist
2009	J	`jnl`	Comparison of Molecular Fingerprint Methods on the Basis of Biological Profile Data. J. Chem. Inf. Model. Andreas Steffen, Thierry Kogej, Christian Tyrchan, Ola Engkvist
2009	J	`jnl`	ProSAR: A New Methodology for Combinatorial Library Design. J. Chem. Inf. Model. Hongming Chen, Ulf Borjesson, Ola Engkvist, Thierry Kogej, Mats Svensson, Niklas Blomberg, Dirk Weigelt, Jeremy N. Burrows, Tim Lange
2006	J	`jnl`	Multifingerprint Based Similarity Searches for Targeted Class Compound Selection. J. Chem. Inf. Model. Thierry Kogej, Ola Engkvist, Niklas Blomberg, Sorel Muresan
2003	J	`jnl`	Prediction of CNS Activity of Compound Libraries Using Substructure Analysis. J. Chem. Inf. Comput. Sci. Ola Engkvist, Paul Wrede, Ulrich Rester
2002	J	`jnl`	High-Throughput, In Silico Prediction of Aqueous Solubility Based on One- and Two-Dimensional Descriptors. J. Chem. Inf. Comput. Sci. Ola Engkvist, Paul Wrede
1998	J	`jnl`	Theoretical study of intermolecular potential energy surface for HCl dimer: Example of nonspherical atom-atom exchange repulsion interaction. J. Comput. Chem. Jose Manuel Hermida-Ramón, Ola Engkvist, Gunnar Karlström
1996	J	`jnl`	On the Relation between Retention Indexes and the Interaction between the Solute and the Column in Gas-Liquid Chromatography. J. Chem. Inf. Comput. Sci. Ola Engkvist, Piotr Borowski, Agneta Bemgård, Gunnar Karlström, Roland Lindh, Anders Colmsjö