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CORDIS

Advanced machine learning for Innovative Drug Discovery

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Deliverables

First newsletter (opens in new window)

Publication of the first newsletter

Publications

Equivariant Graph Neural Networks for Toxicity Prediction (opens in new window)

Author(s): Julian Cremer, Leonardo Medrano Sandonas, Alexandre Tkatchenko, Djork-Arné Clevert, Gianni De Fabritiis
Published in: Chemical Research in Toxicology, 2023, ISSN 0893-228X
Publisher: American Chemical Society
DOI: 10.1021/acs.chemrestox.3c00032

Developing novel Lin28 inhibitors by computer aided drug design (opens in new window)

Author(s): Xuesen Dong, Victor Barrios, Mariia Radaeva, Graciella Rosellinny, Qiongqiong Jia, Ning Xie, Jason Smith, Martin Gleave, Nada Lallous, Artem Cherkasov, Hanadi Ibrahim, Monica Villanueva, Suzana Straus
Published in: Cell Death Discovery, 2025, ISSN 2058-7716
Publisher: Nature Publishing Group
DOI: 10.21203/rs.3.rs-4644460/v1

The openOCHEM consensus model is the best-performing open-source predictive model in the First EUOS/SLAS joint compound solubility challenge (opens in new window)

Author(s): Andrea Hunklinger, Peter Hartog, Martin Šícho, Guillaume Godin, Igor V. Tetko
Published in: SLAS Discovery, Issue 29, 2024, Page(s) 100144, ISSN 2472-5552
Publisher: Elsevier BV
DOI: 10.1016/j.slasd.2024.01.005

HyperPCM: Robust Task-Conditioned Modeling of Drug–Target Interactions (opens in new window)

Author(s): Emma Svensson, Pieter-Jan Hoedt, Sepp Hochreiter, Günter Klambauer
Published in: Journal of Chemical Information and Modeling, Issue 64, 2024, Page(s) 2539-2553, ISSN 1549-9596
Publisher: American Chemical Society
DOI: 10.1021/acs.jcim.3c01417

Using test-time augmentation to investigate explainable AI: inconsistencies between method, model and human intuition (opens in new window)

Author(s): Peter B. R. Hartog, Fabian Krüger, Samuel Genheden, Igor V. Tetko
Published in: Journal of Cheminformatics, 2024, ISSN 1758-2946
Publisher: Chemistry Central
DOI: 10.26434/chemrxiv-2024-kdx3g

Modeling noncovalent interatomic interactions on a photonic quantum computer (opens in new window)

Author(s): Matthieu Sarkis, Alessio Fallani, Alexandre Tkatchenko
Published in: Physical Review Research, Issue 5, 2023, ISSN 2643-1564
Publisher: American Physical Society (APS)
DOI: 10.1103/physrevresearch.5.043072

Pretraining graph transformers with atom-in-a-molecule quantum properties for improved ADMET modeling (opens in new window)

Author(s): Alessio Fallani, Ramil Nugmanov, Jose Arjona-Medina, Jörg Kurt Wegner, Alexandre Tkatchenko, Kostiantyn Chernichenko
Published in: Journal of Cheminformatics, Issue 17, 2025, ISSN 1758-2946
Publisher: Chemistry Central
DOI: 10.1186/s13321-025-00970-0

AlphaFold Meets De Novo Drug Design: Leveraging Structural Protein Information in Multitarget Molecular Generative Models (opens in new window)

Author(s): Andrius Bernatavicius, Martin Šícho, Antonius P. A. Janssen, Alan Kai Hassen, Mike Preuss, Gerard J. P. van Westen
Published in: Journal of Chemical Information and Modeling, Issue 64, 2024, Page(s) 8113-8122, ISSN 1549-9596
Publisher: American Chemical Society
DOI: 10.1021/acs.jcim.4c00309

Investigations into the efficiency of computer-aided synthesis planning (opens in new window)

Author(s): Peter B.R. Hartog, Annie M. Westerlund, Igor V. Tetko, Samuel Genheden
Published in: Journal of Chemical Information and Modeling, 2024, ISSN 1549-9596
Publisher: American Chemical Society
DOI: 10.26434/chemrxiv-2024-q2v87

Unsupervised Representation Learning for Proteochemometric Modeling

Author(s): Kim, PT., Winter, R., Clevert, DA.
Published in: INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, 2021, ISSN 1422-0067
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)

Improving route development using convergent retrosynthesis planning (opens in new window)

Author(s): Paula Torren-Peraire, Jonas Verhoeven, Dorota Herman, Hugo Ceulemans, Igor V. Tetko, Jörg K. Wegner
Published in: Journal of Cheminformatics, Issue 17, 2025, ISSN 1758-2946
Publisher: Chemistry Central
DOI: 10.1186/s13321-025-00953-1

Development of Novel Inhibitors Targeting the D-Box of the DNA Binding Domain of Androgen Receptor (opens in new window)

Author(s): Radaeva, M., Ban, F., Zhang, F., LeBlanc, E., Lallous, N., Rennie, P.S., Gleave, M.E., Cherkasov, A.
Published in: Int. J. Mol. Sci., 2021, Page(s) 2493, ISSN 1422-0067
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/ijms22052493

Img2Mol – accurate SMILES recognition from molecular graphical depictions (opens in new window)

Author(s): Clevert, DA., Le, T., Winter, R., Montanari, F.
Published in: CHEMICAL SCIENCE, 2021, ISSN 2041-6520
Publisher: Royal Society of Chemistry
DOI: 10.1039/d1sc01839f

Generate what you can make: achieving in-house synthesizability with readily available resources in de novo drug design (opens in new window)

Author(s): Alan Kai Hassen, Martin Šícho, Yorick J. van Aalst, Mirjam C. W. Huizenga, Darcy N. R. Reynolds, Sohvi Luukkonen, Andrius Bernatavicius, Djork-Arné Clevert, Antonius P. A. Janssen, Gerard J. P. van Westen, Mike Preuss
Published in: Journal of Cheminformatics, Issue 17, 2025, ISSN 1758-2946
Publisher: Chemistry Central
DOI: 10.1186/s13321-024-00910-4

The Promise of AI for DILI Prediction (opens in new window)

Author(s): Vall, A., Sabnis, Y., Shi, J., Class, R., Hochreiter, S., Klambauer, G.
Published in: Front. Artif. Intell., 2021, ISSN 0922-6389
Publisher: IOS Press
DOI: 10.3389/frai.2021.638410

Expanding the chemical space using a chemical reaction knowledge graph (opens in new window)

Author(s): Emma Rydholm, Tomas Bastys, Emma Svensson, Christos Kannas, Ola Engkvist, Thierry Kogej
Published in: Digital Discovery, Issue 3, 2024, Page(s) 1378-1388, ISSN 2635-098X
Publisher: Royal Society of Chemistry (RSC)
DOI: 10.1039/d3dd00230f

CLOOME: contrastive learning unlocks bioimaging databases for queries with chemical structures (opens in new window)

Author(s): Ana Sanchez-Fernandez, Elisabeth Rumetshofer, Sepp Hochreiter, Günter Klambauer
Published in: Nature Communications, Issue 14, 2023, ISSN 2041-1723
Publisher: Nature Publishing Group
DOI: 10.1038/s41467-023-42328-w

Statistical approaches enabling technology-specific assay interference prediction from large screening data sets (opens in new window)

Author(s): Vincenzo Palmacci, Steffen Hirte, Jorge Enrique Hernández González, Floriane Montanari, Johannes Kirchmair
Published in: Artificial Intelligence in the Life Sciences, Issue 5, 2024, Page(s) 100099, ISSN 2667-3185
Publisher: Elsevier BV
DOI: 10.1016/j.ailsci.2024.100099

Multi-objective synthesis planning by means of Monte Carlo Tree search (opens in new window)

Author(s): Helen Lai, Christos Kannas, Alan Kai Hassen, Emma Granqvist, Annie M. Westerlund, Djork-Arné Clevert, Mike Preuss, Samuel Genheden
Published in: Artificial Intelligence in the Life Sciences, Issue 7, 2025, Page(s) 100130, ISSN 2667-3185
Publisher: Elsevier BV
DOI: 10.1016/j.ailsci.2025.100130

Molecular property prediction using pretrained-BERT and Bayesian active learning: a data-efficient approach to drug design (opens in new window)

Author(s): Muhammad Arslan Masood, Samuel Kaski, Tianyu Cui
Published in: Journal of Cheminformatics, Issue 17, 2025, ISSN 1758-2946
Publisher: Chemistry Central
DOI: 10.1186/s13321-025-00986-6

Dataset for quantum-mechanical exploration of conformers and solvent effects in large drug-like molecules (opens in new window)

Author(s): Leonardo Medrano Sandonas, Dries Van Rompaey, Alessio Fallani, Mathias Hilfiker, David Hahn, Laura Perez-Benito, Jonas Verhoeven, Gary Tresadern, Joerg Kurt Wegner, Hugo Ceulemans, Alexandre Tkatchenko
Published in: Scientific Data, Issue 11, 2024, ISSN 2052-4463
Publisher: Springer Science and Business Media LLC
DOI: 10.1038/s41597-024-03521-8

Inverse mapping of quantum properties to structures for chemical space of small organic molecules (opens in new window)

Author(s): Alessio Fallani, Leonardo Medrano Sandonas, Alexandre Tkatchenko
Published in: Nature Communications, Issue 15, 2024, ISSN 2041-1723
Publisher: Nature Publishing Group
DOI: 10.1038/s41467-024-50401-1

Domain Shifts in Machine Learning Based Covid-19 Diagnosis From Blood Tests (opens in new window)

Author(s): Roland, T., Bock, C., Tschoellitsch, T., Maletzky, A., Hochreiter, S., Meier, J., Klambauer, G.
Published in: JOURNAL OF MEDICAL SYSTEMS, 2022, ISSN 0148-5598
Publisher: Kluwer Academic/Plenum Publishers
DOI: 10.1007/s10916-022-01807-1

Models Matter: the impact of single-step retrosynthesis on synthesis planning (opens in new window)

Author(s): Paula Torren-Peraire, Alan Kai Hassen, Samuel Genheden, Jonas Verhoeven, Djork-Arné Clevert, Mike Preuss, Igor V. Tetko
Published in: Digital Discovery, Issue 3, 2024, Page(s) 558-572, ISSN 2635-098X
Publisher: Royal Society of Chemistry (RSC)
DOI: 10.1039/d3dd00252g

Decoding phenotypic screening: A comparative analysis of image representations (opens in new window)

Author(s): Adriana Borowa, Dawid Rymarczyk, Marek Żyła, Maciej Kańduła, Ana Sánchez-Fernández, Krzysztof Rataj, Łukasz Struski, Jacek Tabor, Bartosz Zieliński
Published in: Computational and Structural Biotechnology Journal, Issue 23, 2025, Page(s) 1181-1188, ISSN 2001-0370
Publisher: Elsevier BV
DOI: 10.1016/j.csbj.2024.02.022

A note on leveraging synergy in multiple meteorological data sets with deep learning for rainfall-runoff modeling (opens in new window)

Author(s): Kratzert, F., Klotz, D., Hochreiter, S., Nearing, GS.
Published in: HYDROLOGY AND EARTH SYSTEM SCIENCES, 2021, ISSN 1027-5606
Publisher: European Geophysical Society
DOI: 10.5194/hess-25-2685-2021

Accelerating the inference of string generation-based chemical reaction models for industrial applications (opens in new window)

Author(s): Mikhail Andronov, Natalia Andronova, Michael Wand, Jürgen Schmidhuber, Djork-Arné Clevert
Published in: Journal of Cheminformatics, Issue 17, 2025, ISSN 1758-2946
Publisher: Chemistry Central
DOI: 10.1186/s13321-025-00974-w

When Yield Prediction Does Not Yield Prediction: An Overview of the Current Challenges (opens in new window)

Author(s): Varvara Voinarovska, Mikhail Kabeshov, Dmytro Dudenko, Samuel Genheden, Igor V. Tetko
Published in: Journal of Chemical Information and Modeling, Issue 64, 2024, Page(s) 42-56, ISSN 1549-9596
Publisher: American Chemical Society
DOI: 10.1021/acs.jcim.3c01524

Metis: a python-based user interface to collect expert feedback for generative chemistry models (opens in new window)

Author(s): Janosch Menke, Yasmine Nahal, Esben Jannik Bjerrum, Mikhail Kabeshov, Samuel Kaski, Ola Engkvist
Published in: Journal of Cheminformatics, Issue 16, 2024, ISSN 1758-2946
Publisher: Chemistry Central
DOI: 10.1186/s13321-024-00892-3

Equivariant diffusion for structure-based de novo ligand generation with latent-conditioning (opens in new window)

Author(s): Tuan Le, Julian Cremer, Djork-Arné Clevert, Kristof T. Schütt
Published in: Journal of Cheminformatics, Issue 17, 2025, ISSN 1758-2946
Publisher: Chemistry Central
DOI: 10.1186/s13321-025-01028-x

Low Concentration Cell Painting Images Enable the Identification of Highly Potent Compounds (opens in new window)

Author(s): Son V. Ha, Steffen Jaensch, Lorena G. A. Freitas, Dorota Herman, Paul Czodrowski, Hugo Ceulemans
Published in: Scientific Reports, 2024, ISSN 2045-2322
Publisher: Nature Publishing Group
DOI: 10.21203/rs.3.rs-4466969/v1

Rainfall-runoff prediction at multiple timescales with a single Long Short-Term Memory network (opens in new window)

Author(s): Gauch, M., Kratzert, F., Klotz, D., Nearing, G., Lin, J., Hochreiter, S.
Published in: HYDROLOGY AND EARTH SYSTEM SCIENCES, 2021, ISSN 1027-5606
Publisher: European Geophysical Society
DOI: 10.5194/hess-25-2045-2021

Reagent Prediction with a Molecular Transformer Improves Reaction Data Quality (opens in new window)

Author(s): Andronov, M., Voinarovska, V., Andronova, N., Wand, M., Clevert, D.-A., Schmidhuber, J.
Published in: Chemical Science, 2023, ISSN 2573-2293
Publisher: Royal Society of Chemistry
DOI: 10.1039/d2sc06798f

FSL-CP: a benchmark for small molecule activity few-shot prediction using cell microscopy images (opens in new window)

Author(s): Son V. Ha, Lucas Leuschner, Paul Czodrowski
Published in: Digital Discovery, Issue 3, 2024, Page(s) 719-727, ISSN 2635-098X
Publisher: Royal Society of Chemistry (RSC)
DOI: 10.1039/d3dd00205e

Enhancing uncertainty quantification in drug discovery with censored regression labels (opens in new window)

Author(s): Emma Svensson, Hannah Rosa Friesacher, Susanne Winiwarter, Lewis Mervin, Adam Arany, Ola Engkvist
Published in: Artificial Intelligence in the Life Sciences, Issue 7, 2025, Page(s) 100128, ISSN 2667-3185
Publisher: Elsevier BV
DOI: 10.1016/j.ailsci.2025.100128

Achieving well-informed decision-making in drug discovery: a comprehensive calibration study using neural network-based structure-activity models (opens in new window)

Author(s): Hannah Rosa Friesacher, Ola Engkvist, Lewis Mervin, Yves Moreau, Adam Arany
Published in: Journal of Cheminformatics, Issue 17, 2025, ISSN 1758-2946
Publisher: Chemistry Central
DOI: 10.1186/s13321-025-00964-y

E-GuARD: expert-guided augmentation for the robust detection of compounds interfering with biological assays (opens in new window)

Author(s): Vincenzo Palmacci, Yasmine Nahal, Matthias Welsch, Ola Engkvist, Samuel Kaski, Johannes Kirchmair
Published in: Journal of Cheminformatics, Issue 17, 2025, ISSN 1758-2946
Publisher: Chemistry Central
DOI: 10.1186/s13321-025-01014-3

AiZynthFinder 4.0: developments based on learnings from 3 years of industrial application (opens in new window)

Author(s): Lakshidaa Saigiridharan, Alan Kai Hassen, Helen Lai, Paula Torren-Peraire, Ola Engkvist, Samuel Genheden
Published in: Journal of Cheminformatics, Issue 16, 2024, ISSN 1758-2946
Publisher: Chemistry Central
DOI: 10.1186/s13321-024-00860-x

Uncertainty estimation with deep learning for rainfall-runoff modeling (opens in new window)

Author(s): Klotz, D., Kratzert, F., Gauch, M., Sampson, AK., Brandstetter, J., Klambauer, G., Hochreiter, S., Nearing, G.
Published in: HYDROLOGY AND EARTH SYSTEM SCIENCES, 2022, ISSN 1027-5606
Publisher: European Geophysical Society
DOI: 10.5194/hess-26-1673-2022

Human-in-the-loop active learning for goal-oriented molecule generation (opens in new window)

Author(s): Yasmine Nahal, Janosch Menke, Julien Martinelli, Markus Heinonen, Mikhail Kabeshov, Jon Paul Janet, Eva Nittinger, Ola Engkvist, Samuel Kaski
Published in: Journal of Cheminformatics, Issue 16, 2024, ISSN 1758-2946
Publisher: Chemistry Central
DOI: 10.1186/s13321-024-00924-y

PILOT: equivariant diffusion for pocket-conditioned <i>de novo</i> ligand generation with multi-objective guidance <i>via</i> importance sampling (opens in new window)

Author(s): Julian Cremer, Tuan Le, Frank Noé, Djork-Arné Clevert, Kristof T. Schütt
Published in: Chemical Science, Issue 15, 2024, Page(s) 14954-14967, ISSN 2041-6520
Publisher: Royal Society of Chemistry
DOI: 10.1039/d4sc03523b

Mind the Retrosynthesis Gap: Bridging the divide between Single-step and Multi-step Retrosynthesis Prediction

Author(s): Alan Kai Hassen, Paula Torren-Peraire, Samuel Genheden, Jonas Verhoeven, Mike Preuss, Igor V. Tetko
Published in: NeurIPS 2022 Workshop AI4Science, 2022
Publisher: OpenReview.net

Robust Task-Specific Adaption of Models for Drug-Target Interaction Prediction (opens in new window)

Author(s): Svensson, E., Hoedt, P.-J., Hochreiter, S., Klambauer, G.
Published in: 36th Conference on Neural Information Processing Systems (NeurIPS 2022), 2022
Publisher: NeurIPS 2022
DOI: 10.5281/zenodo.8138500

Multi-Modal Representation learning for molecules (opens in new window)

Author(s): Muhammad Arslan Masood, Markus Heinonen, Samuel Kaski
Published in: ICLR 2025 Workshop LMRL, 2025
Publisher: OpenReview.net
DOI: 10.5281/zenodo.15484224

Navigating the Design Space of Equivariant Diffusion-Based Generative Models for De Novo 3D Molecule Generation (opens in new window)

Author(s): Tuan Le, Julian Cremer, Frank Noé, Djork-Arné Clevert, Kristof Schütt
Published in: ICLR 2024, 2024
Publisher: arXiv
DOI: 10.48550/arxiv.2309.17296

Contrastive Learning of Image- and Structure-Based Representations in Drug Discovery (opens in new window)

Author(s): Sanchez-Fernandez, A., Rumetshofer, E., Hochreiter, S., Klambauer, G.
Published in: International Conference on Learning Representations, 2022
Publisher: MLDD workshop, ICLR 2022
DOI: 10.5281/zenodo.8137823

MC-LSTM: Mass-Conserving LSTM (opens in new window)

Author(s): Hoedt, PJ., Kratzert, F., Klotz, D., Halmich, C., Holzleitner, M., Nearing, G., Hochreiter, S., Klambauer, G.
Published in: INTERNATIONAL CONFERENCE ON MACHINE LEARNING, 2021, ISSN 2640-3498
Publisher: Cambridge MA: JMLR
DOI: 10.5281/zenodo.8138359

Expressive Graph Informer Networks (opens in new window)

Author(s): Simm, J., Arany, A., De Brouwer, E., Moreau, Y.
Published in: MACHINE LEARNING, OPTIMIZATION, AND DATA SCIENCE (LOD 2021), PT II, Book Series Title: Lecture Notes in Computer Science, 2022, ISSN 0302-9743
Publisher: Springer Verlag
DOI: 10.1007/978-3-030-95470-3_15

A reagent-driven visual method for analyzing chemical reaction data (opens in new window)

Author(s): Mikhail Andronov, Natalia Andronova, Michael Wand, Jürgen Schmidhuber, Djork-Arné Clevert
Published in: arXiv preprint, 2024
Publisher: ChemRxiv
DOI: 10.26434/chemrxiv-2024-q9tc4

Modeling Non-Covalent Interatomic Interactions on a Photonic Quantum Computer (opens in new window)

Author(s): Sarkis, M., Fallani, A.,Tkatchenko, A.
Published in: 2023
Publisher: arXiv
DOI: 10.48550/arxiv.2306.08544

NETWORK ANALYSIS OF THE ORGANIC CHEMISTRY IN PATENTS, LITERATURE, AND PHARMACEUTICAL INDUSTRY (opens in new window)

Author(s): Thierry Kogej, Emma Svensson, Emma Rydholm, Tomas Bastys, Christos Kannas, Mikhail Kabeshov, Samuel Genheden, Ola Engkvist
Published in: Chemrxiv, Issue Chemrxiv, 2024
Publisher: ChemRxiv
DOI: 10.26434/chemrxiv-2024-h4qlt

Temporal Distribution Shift in Real-World Pharmaceutical Data: Implications for Uncertainty Quantification in QSAR Models (opens in new window)

Author(s): Hannah Rosa Friesacher, Emma Svensson, Susanne Winiwarter, Lewis Mervin, Adam Arany, Ola Engkvist
Published in: arXiv preprint, 2025
Publisher: arXiv
DOI: 10.48550/arxiv.2502.03982

openOCHEM consensus model wins Kaggle First EUOS/SLAS Joint Compound Solubility Challenge (opens in new window)

Author(s): Kopp, A., Hartog, P., Šícho, M., Godin, G., Tetko, I.V.
Published in: 2023
Publisher: ChemRxiv
DOI: 10.26434/chemrxiv-2023-p8qcv

Equivariant Graph Neural Networks for Toxicity Prediction (opens in new window)

Author(s): Cremer, J., Medrano Sandonas, L., Tkatchenko, A., Clevert, D.A., De Fabritiis, G.
Published in: 2023, ISSN 2573-2293
Publisher: ChemRxiv
DOI: 10.26434/chemrxiv-2023-9kb55

Temporal Evaluation of Probability Calibration with Experimental Errors (opens in new window)

Author(s): Hannah Rosa Friesacher, Emma Svensson, Adam Arany, Lewis Mervin, Ola Engkvist
Published in: Lecture Notes in Computer Science, AI in Drug Discovery, 2024, Page(s) 13-20
Publisher: Springer Nature Switzerland
DOI: 10.1007/978-3-031-72381-0_2

Latent-Conditioned Equivariant Diffusion for Structure-Based De Novo Ligand Generation (opens in new window)

Author(s): Julian Cremer, Tuan Le, Djork-Arné Clevert, Kristof T. Schütt
Published in: Lecture Notes in Computer Science, AI in Drug Discovery, 2024, Page(s) 36-46
Publisher: Springer Nature Switzerland
DOI: 10.1007/978-3-031-72381-0_4

Atom-Level Quantum Pretraining Enhances the Spectral Perception of Molecular Graphs in Graphormer (opens in new window)

Author(s): Alessio Fallani, José Arjona-Medina, Konstantin Chernichenko, Ramil Nugmanov, Jörg Kurt Wegner, Alexandre Tkatchenko
Published in: Lecture Notes in Computer Science, AI in Drug Discovery, 2024, Page(s) 71-81
Publisher: Springer Nature Switzerland
DOI: 10.1007/978-3-031-72381-0_7

Towards Interpretable Models of Chemist Preferences for Human-in-the-Loop Assisted Drug Discovery (opens in new window)

Author(s): Yasmine Nahal, Markus Heinonen, Mikhail Kabeshov, Jon Paul Janet, Eva Nittinger, Ola Engkvist, Samuel Kaski
Published in: Lecture Notes in Computer Science, AI in Drug Discovery, 2024, Page(s) 58-70
Publisher: Springer Nature Switzerland
DOI: 10.1007/978-3-031-72381-0_6

Balancing Imbalanced Toxicity Models: Using MolBERT with Focal Loss (opens in new window)

Author(s): Muhammad Arslan Masood, Samuel Kaski, Hugo Ceulemans, Dorota Herman, Markus Heinonen
Published in: Lecture Notes in Computer Science, AI in Drug Discovery, 2024, Page(s) 82-97
Publisher: Springer Nature Switzerland
DOI: 10.1007/978-3-031-72381-0_8

Curating Reagents in Chemical Reaction Data with an Interactive Reagent Space Map (opens in new window)

Author(s): Mikhail Andronov, Natalia Andronova, Michael Wand, Jürgen Schmidhuber, Djork-Arné Clevert
Published in: Lecture Notes in Computer Science, AI in Drug Discovery, 2024, Page(s) 21-35
Publisher: Springer Nature Switzerland
DOI: 10.1007/978-3-031-72381-0_3

Temporal Evaluation of Uncertainty Quantification Under Distribution Shift (opens in new window)

Author(s): Emma Svensson, Hannah Rosa Friesacher, Adam Arany, Lewis Mervin, Ola Engkvist
Published in: Lecture Notes in Computer Science, AI in Drug Discovery, 2024, Page(s) 132-148
Publisher: Springer Nature Switzerland
DOI: 10.1007/978-3-031-72381-0_11

Leveraging Quantum Mechanical Properties to Predict Solvent Effects on Large Drug-Like Molecules (opens in new window)

Author(s): Mathias Hilfiker, Leonardo Medrano Sandonas, Marco Klähn, Ola Engkvist, Alexandre Tkatchenko
Published in: Lecture Notes in Computer Science, AI in Drug Discovery, 2024, Page(s) 47-57
Publisher: Springer Nature Switzerland
DOI: 10.1007/978-3-031-72381-0_5

Registries in Machine Learning-Based Drug Discovery: A Shortcut to Code Reuse (opens in new window)

Author(s): Peter B. R. Hartog, Emma Svensson, Lewis Mervin, Samuel Genheden, Ola Engkvist, Igor V. Tetko
Published in: Lecture Notes in Computer Science, AI in Drug Discovery, 2024, Page(s) 98-115
Publisher: Springer Nature Switzerland
DOI: 10.1007/978-3-031-72381-0_9

Deep Bayesian Experimental Design for Drug Discovery (opens in new window)

Author(s): Muhammad Arslan Masood, Tianyu Cui, Samuel Kaski
Published in: Lecture Notes in Computer Science, AI in Drug Discovery, 2024, Page(s) 149-159
Publisher: Springer Nature Switzerland
DOI: 10.1007/978-3-031-72381-0_12

Current Limitations of Text-based Molecular Representations for Machine Learning in Small Molecule Drug Discovery

Author(s): Peter Bart Rudolf Hartog
Published in: Doctoral thesis, 2025
Publisher: TUM School of Life Sciences

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