Advanced machine learning for Innovative Drug Discovery

CORDIS oferuje możliwość skorzystania z odnośników do publicznie dostępnych publikacji i rezultatów projektów realizowanych w ramach programów ramowych HORYZONT.

Odnośniki do rezultatów i publikacji związanych z poszczególnymi projektami 7PR, a także odnośniki do niektórych konkretnych kategorii wyników, takich jak zbiory danych i oprogramowanie, są dynamicznie pobierane z systemu OpenAIRE .

Rezultaty

Software for retrosynthesis

Publicly available source code for chemical retrosynthesis

First newsletter

Publication of the first newsletter

ML toolbox for QM property prediction

Open source Machine Learning (ML) toolbox for Quantum Mechanics (QM) property prediction

One Chemistry model

"Source code of the ""One Chemistry"" that combines individual developments of others ESRs"

Modular AI systems

Methodology and source code for robust training of modular AI systems

Software for phenotypic screening

Open source software for phenotypic screening predictions with confidence estimation

Use of human knowledge for models development

Methodology to improve machine learning models in drug discovery with human knowledge

SS2 school report
Recruitment meeting

Minutes of the recruitment meeting

Minutes of the kick-off meeting
SS3 school report
Communication and public engagement activities

Overview of communication and public engagement activities

Final conference

Final conference report

SS1 school report

Web site

The web site and web application system is established

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Publikacje

Equivariant Graph Neural Networks for Toxicity Prediction

Autorzy: Julian Cremer, Leonardo Medrano Sandonas, Alexandre Tkatchenko, Djork-Arné Clevert, Gianni De Fabritiis
Opublikowane w: Chemical Research in Toxicology, 2023, ISSN 0893-228X
Wydawca: American Chemical Society
DOI: 10.1021/acs.chemrestox.3c00032

Developing novel Lin28 inhibitors by computer aided drug design

Autorzy: 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
Opublikowane w: Cell Death Discovery, 2025, ISSN 2058-7716
Wydawca: 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

Autorzy: Andrea Hunklinger, Peter Hartog, Martin Šícho, Guillaume Godin, Igor V. Tetko
Opublikowane w: SLAS Discovery, Numer 29, 2024, Strona(/y) 100144, ISSN 2472-5552
Wydawca: Elsevier BV
DOI: 10.1016/j.slasd.2024.01.005

HyperPCM: Robust Task-Conditioned Modeling of Drug–Target Interactions

Autorzy: Emma Svensson, Pieter-Jan Hoedt, Sepp Hochreiter, Günter Klambauer
Opublikowane w: Journal of Chemical Information and Modeling, Numer 64, 2024, Strona(/y) 2539-2553, ISSN 1549-9596
Wydawca: American Chemical Society
DOI: 10.1021/acs.jcim.3c01417

Using test-time augmentation to investigate explainable AI: inconsistencies between method, model and human intuition

Autorzy: Peter B. R. Hartog, Fabian Krüger, Samuel Genheden, Igor V. Tetko
Opublikowane w: Journal of Cheminformatics, 2024, ISSN 1758-2946
Wydawca: Chemistry Central
DOI: 10.26434/chemrxiv-2024-kdx3g

Modeling noncovalent interatomic interactions on a photonic quantum computer

Autorzy: Matthieu Sarkis, Alessio Fallani, Alexandre Tkatchenko
Opublikowane w: Physical Review Research, Numer 5, 2023, ISSN 2643-1564
Wydawca: American Physical Society (APS)
DOI: 10.1103/physrevresearch.5.043072

Pretraining graph transformers with atom-in-a-molecule quantum properties for improved ADMET modeling

Autorzy: Alessio Fallani, Ramil Nugmanov, Jose Arjona-Medina, Jörg Kurt Wegner, Alexandre Tkatchenko, Kostiantyn Chernichenko
Opublikowane w: Journal of Cheminformatics, Numer 17, 2025, ISSN 1758-2946
Wydawca: Chemistry Central
DOI: 10.1186/s13321-025-00970-0

AlphaFold Meets De Novo Drug Design: Leveraging Structural Protein Information in Multitarget Molecular Generative Models

Autorzy: Andrius Bernatavicius, Martin Šícho, Antonius P. A. Janssen, Alan Kai Hassen, Mike Preuss, Gerard J. P. van Westen
Opublikowane w: Journal of Chemical Information and Modeling, Numer 64, 2024, Strona(/y) 8113-8122, ISSN 1549-9596
Wydawca: American Chemical Society
DOI: 10.1021/acs.jcim.4c00309

Investigations into the efficiency of computer-aided synthesis planning

Autorzy: Peter B.R. Hartog, Annie M. Westerlund, Igor V. Tetko, Samuel Genheden
Opublikowane w: Journal of Chemical Information and Modeling, 2024, ISSN 1549-9596
Wydawca: American Chemical Society
DOI: 10.26434/chemrxiv-2024-q2v87

Unsupervised Representation Learning for Proteochemometric Modeling

Autorzy: Kim, PT., Winter, R., Clevert, DA.
Opublikowane w: INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, 2021, ISSN 1422-0067
Wydawca: Multidisciplinary Digital Publishing Institute (MDPI)

Improving route development using convergent retrosynthesis planning

Autorzy: Paula Torren-Peraire, Jonas Verhoeven, Dorota Herman, Hugo Ceulemans, Igor V. Tetko, Jörg K. Wegner
Opublikowane w: Journal of Cheminformatics, Numer 17, 2025, ISSN 1758-2946
Wydawca: 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

Autorzy: Radaeva, M., Ban, F., Zhang, F., LeBlanc, E., Lallous, N., Rennie, P.S., Gleave, M.E., Cherkasov, A.
Opublikowane w: Int. J. Mol. Sci., 2021, Strona(/y) 2493, ISSN 1422-0067
Wydawca: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/ijms22052493

Img2Mol – accurate SMILES recognition from molecular graphical depictions

Autorzy: Clevert, DA., Le, T., Winter, R., Montanari, F.
Opublikowane w: CHEMICAL SCIENCE, 2021, ISSN 2041-6520
Wydawca: 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

Autorzy: 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
Opublikowane w: Journal of Cheminformatics, Numer 17, 2025, ISSN 1758-2946
Wydawca: Chemistry Central
DOI: 10.1186/s13321-024-00910-4

Be aware of overfitting by hyperparameter optimization!

Autorzy: Igor V. Tetko, Ruud van Deursen, Guillaume Godin
Opublikowane w: Journal of Cheminformatics, Numer 16, 2024, ISSN 1758-2946
Wydawca: Chemistry Central
DOI: 10.1186/s13321-024-00934-w

The Promise of AI for DILI Prediction

Autorzy: Vall, A., Sabnis, Y., Shi, J., Class, R., Hochreiter, S., Klambauer, G.
Opublikowane w: Front. Artif. Intell., 2021, ISSN 0922-6389
Wydawca: IOS Press
DOI: 10.3389/frai.2021.638410

Expanding the chemical space using a chemical reaction knowledge graph

Autorzy: Emma Rydholm, Tomas Bastys, Emma Svensson, Christos Kannas, Ola Engkvist, Thierry Kogej
Opublikowane w: Digital Discovery, Numer 3, 2024, Strona(/y) 1378-1388, ISSN 2635-098X
Wydawca: Royal Society of Chemistry (RSC)
DOI: 10.1039/d3dd00230f

Tackling assay interference associated with small molecules

Autorzy: Lu Tan, Steffen Hirte, Vincenzo Palmacci, Conrad Stork, Johannes Kirchmair
Opublikowane w: Nature Reviews Chemistry, Numer 8, 2024, Strona(/y) 319-339, ISSN 2397-3358
Wydawca: Springer Science and Business Media LLC
DOI: 10.1038/s41570-024-00593-3

Online OCHEM multi-task model for solubility and lipophilicity prediction of platinum complexes

Autorzy: Nesma Mousa, Hristo P. Varbanov, Vidya Kaipanchery, Elisabetta Gabano, Mauro Ravera, Andrey A. Toropov, Larisa Charochkina, Filipe Menezes, Guillaume Godin, Igor V. Tetko
Opublikowane w: Journal of Inorganic Biochemistry, Numer 269, 2025, Strona(/y) 112890, ISSN 0162-0134
Wydawca: Elsevier BV
DOI: 10.1016/j.jinorgbio.2025.112890

CLOOME: contrastive learning unlocks bioimaging databases for queries with chemical structures

Autorzy: Ana Sanchez-Fernandez, Elisabeth Rumetshofer, Sepp Hochreiter, Günter Klambauer
Opublikowane w: Nature Communications, Numer 14, 2023, ISSN 2041-1723
Wydawca: Nature Publishing Group
DOI: 10.1038/s41467-023-42328-w

Statistical approaches enabling technology-specific assay interference prediction from large screening data sets

Autorzy: Vincenzo Palmacci, Steffen Hirte, Jorge Enrique Hernández González, Floriane Montanari, Johannes Kirchmair
Opublikowane w: Artificial Intelligence in the Life Sciences, Numer 5, 2024, Strona(/y) 100099, ISSN 2667-3185
Wydawca: Elsevier BV
DOI: 10.1016/j.ailsci.2024.100099

Multi-objective synthesis planning by means of Monte Carlo Tree search

Autorzy: Helen Lai, Christos Kannas, Alan Kai Hassen, Emma Granqvist, Annie M. Westerlund, Djork-Arné Clevert, Mike Preuss, Samuel Genheden
Opublikowane w: Artificial Intelligence in the Life Sciences, Numer 7, 2025, Strona(/y) 100130, ISSN 2667-3185
Wydawca: Elsevier BV
DOI: 10.1016/j.ailsci.2025.100130

Network Analysis of the Organic Chemistry in Patents, Literature, and Pharmaceutical Industry

Autorzy: Emma Svensson, Emma Granqvist, Tomas Bastys, Christos Kannas, Mikhail Kabeshov, Samuel Genheden, Ola Engkvist, Thierry Kogej
Opublikowane w: Molecular Informatics, Numer 44, 2025, ISSN 1868-1743
Wydawca: Wiley - VCH Verlag GmbH & CO. KGaA
DOI: 10.1002/minf.202500011

Molecular property prediction using pretrained-BERT and Bayesian active learning: a data-efficient approach to drug design

Autorzy: Muhammad Arslan Masood, Samuel Kaski, Tianyu Cui
Opublikowane w: Journal of Cheminformatics, Numer 17, 2025, ISSN 1758-2946
Wydawca: Chemistry Central
DOI: 10.1186/s13321-025-00986-6

Dataset for quantum-mechanical exploration of conformers and solvent effects in large drug-like molecules

Autorzy: 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
Opublikowane w: Scientific Data, Numer 11, 2024, ISSN 2052-4463
Wydawca: 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

Autorzy: Alessio Fallani, Leonardo Medrano Sandonas, Alexandre Tkatchenko
Opublikowane w: Nature Communications, Numer 15, 2024, ISSN 2041-1723
Wydawca: Nature Publishing Group
DOI: 10.1038/s41467-024-50401-1

Domain Shifts in Machine Learning Based Covid-19 Diagnosis From Blood Tests

Autorzy: Roland, T., Bock, C., Tschoellitsch, T., Maletzky, A., Hochreiter, S., Meier, J., Klambauer, G.
Opublikowane w: JOURNAL OF MEDICAL SYSTEMS, 2022, ISSN 0148-5598
Wydawca: Kluwer Academic/Plenum Publishers
DOI: 10.1007/s10916-022-01807-1

Models Matter: the impact of single-step retrosynthesis on synthesis planning

Autorzy: Paula Torren-Peraire, Alan Kai Hassen, Samuel Genheden, Jonas Verhoeven, Djork-Arné Clevert, Mike Preuss, Igor V. Tetko
Opublikowane w: Digital Discovery, Numer 3, 2024, Strona(/y) 558-572, ISSN 2635-098X
Wydawca: Royal Society of Chemistry (RSC)
DOI: 10.1039/d3dd00252g

Decoding phenotypic screening: A comparative analysis of image representations

Autorzy: Adriana Borowa, Dawid Rymarczyk, Marek Żyła, Maciej Kańduła, Ana Sánchez-Fernández, Krzysztof Rataj, Łukasz Struski, Jacek Tabor, Bartosz Zieliński
Opublikowane w: Computational and Structural Biotechnology Journal, Numer 23, 2025, Strona(/y) 1181-1188, ISSN 2001-0370
Wydawca: 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

Autorzy: Kratzert, F., Klotz, D., Hochreiter, S., Nearing, GS.
Opublikowane w: HYDROLOGY AND EARTH SYSTEM SCIENCES, 2021, ISSN 1027-5606
Wydawca: European Geophysical Society
DOI: 10.5194/hess-25-2685-2021

Accelerating the inference of string generation-based chemical reaction models for industrial applications

Autorzy: Mikhail Andronov, Natalia Andronova, Michael Wand, Jürgen Schmidhuber, Djork-Arné Clevert
Opublikowane w: Journal of Cheminformatics, Numer 17, 2025, ISSN 1758-2946
Wydawca: Chemistry Central
DOI: 10.1186/s13321-025-00974-w

When Yield Prediction Does Not Yield Prediction: An Overview of the Current Challenges

Autorzy: Varvara Voinarovska, Mikhail Kabeshov, Dmytro Dudenko, Samuel Genheden, Igor V. Tetko
Opublikowane w: Journal of Chemical Information and Modeling, Numer 64, 2024, Strona(/y) 42-56, ISSN 1549-9596
Wydawca: American Chemical Society
DOI: 10.1021/acs.jcim.3c01524

Metis: a python-based user interface to collect expert feedback for generative chemistry models

Autorzy: Janosch Menke, Yasmine Nahal, Esben Jannik Bjerrum, Mikhail Kabeshov, Samuel Kaski, Ola Engkvist
Opublikowane w: Journal of Cheminformatics, Numer 16, 2024, ISSN 1758-2946
Wydawca: Chemistry Central
DOI: 10.1186/s13321-024-00892-3

Equivariant diffusion for structure-based de novo ligand generation with latent-conditioning

Autorzy: Tuan Le, Julian Cremer, Djork-Arné Clevert, Kristof T. Schütt
Opublikowane w: Journal of Cheminformatics, Numer 17, 2025, ISSN 1758-2946
Wydawca: Chemistry Central
DOI: 10.1186/s13321-025-01028-x

Low Concentration Cell Painting Images Enable the Identification of Highly Potent Compounds

Autorzy: Son V. Ha, Steffen Jaensch, Lorena G. A. Freitas, Dorota Herman, Paul Czodrowski, Hugo Ceulemans
Opublikowane w: Scientific Reports, 2024, ISSN 2045-2322
Wydawca: Nature Publishing Group
DOI: 10.21203/rs.3.rs-4466969/v1

Temporal distribution shift in real-world pharmaceutical data: Implications for uncertainty quantification in QSAR models

Autorzy: Hannah Rosa Friesacher, Emma Svensson, Susanne Winiwarter, Lewis Mervin, Adam Arany, Ola Engkvist
Opublikowane w: Artificial Intelligence in the Life Sciences, Numer 8, 2025, Strona(/y) 100132, ISSN 2667-3185
Wydawca: Elsevier BV
DOI: 10.1016/j.ailsci.2025.100132

Rainfall-runoff prediction at multiple timescales with a single Long Short-Term Memory network

Autorzy: Gauch, M., Kratzert, F., Klotz, D., Nearing, G., Lin, J., Hochreiter, S.
Opublikowane w: HYDROLOGY AND EARTH SYSTEM SCIENCES, 2021, ISSN 1027-5606
Wydawca: European Geophysical Society
DOI: 10.5194/hess-25-2045-2021

Reagent Prediction with a Molecular Transformer Improves Reaction Data Quality

Autorzy: Andronov, M., Voinarovska, V., Andronova, N., Wand, M., Clevert, D.-A., Schmidhuber, J.
Opublikowane w: Chemical Science, 2023, ISSN 2573-2293
Wydawca: Royal Society of Chemistry
DOI: 10.1039/d2sc06798f

FSL-CP: a benchmark for small molecule activity few-shot prediction using cell microscopy images

Autorzy: Son V. Ha, Lucas Leuschner, Paul Czodrowski
Opublikowane w: Digital Discovery, Numer 3, 2024, Strona(/y) 719-727, ISSN 2635-098X
Wydawca: Royal Society of Chemistry (RSC)
DOI: 10.1039/d3dd00205e

Enhancing uncertainty quantification in drug discovery with censored regression labels

Autorzy: Emma Svensson, Hannah Rosa Friesacher, Susanne Winiwarter, Lewis Mervin, Adam Arany, Ola Engkvist
Opublikowane w: Artificial Intelligence in the Life Sciences, Numer 7, 2025, Strona(/y) 100128, ISSN 2667-3185
Wydawca: 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

Autorzy: Hannah Rosa Friesacher, Ola Engkvist, Lewis Mervin, Yves Moreau, Adam Arany
Opublikowane w: Journal of Cheminformatics, Numer 17, 2025, ISSN 1758-2946
Wydawca: Chemistry Central
DOI: 10.1186/s13321-025-00964-y

E-GuARD: expert-guided augmentation for the robust detection of compounds interfering with biological assays

Autorzy: Vincenzo Palmacci, Yasmine Nahal, Matthias Welsch, Ola Engkvist, Samuel Kaski, Johannes Kirchmair
Opublikowane w: Journal of Cheminformatics, Numer 17, 2025, ISSN 1758-2946
Wydawca: Chemistry Central
DOI: 10.1186/s13321-025-01014-3

AiZynthFinder 4.0: developments based on learnings from 3 years of industrial application

Autorzy: Lakshidaa Saigiridharan, Alan Kai Hassen, Helen Lai, Paula Torren-Peraire, Ola Engkvist, Samuel Genheden
Opublikowane w: Journal of Cheminformatics, Numer 16, 2024, ISSN 1758-2946
Wydawca: Chemistry Central
DOI: 10.1186/s13321-024-00860-x

Uncertainty estimation with deep learning for rainfall-runoff modeling

Autorzy: Klotz, D., Kratzert, F., Gauch, M., Sampson, AK., Brandstetter, J., Klambauer, G., Hochreiter, S., Nearing, G.
Opublikowane w: HYDROLOGY AND EARTH SYSTEM SCIENCES, 2022, ISSN 1027-5606
Wydawca: European Geophysical Society
DOI: 10.5194/hess-26-1673-2022

Development of Novel Inhibitors Targeting the D-Box of the DNA Binding Domain of Androgen Receptor

Autorzy: Mariia Radaeva, Fuqiang Ban, Fan Zhang, Eric LeBlanc, Nada Lallous, Paul S. Rennie, Martin E. Gleave, Artem Cherkasov
Opublikowane w: International Journal of Molecular Sciences, Numer 22, 2025, Strona(/y) 2493, ISSN 1422-0067
Wydawca: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/ijms22052493

Human-in-the-loop active learning for goal-oriented molecule generation

Autorzy: Yasmine Nahal, Janosch Menke, Julien Martinelli, Markus Heinonen, Mikhail Kabeshov, Jon Paul Janet, Eva Nittinger, Ola Engkvist, Samuel Kaski
Opublikowane w: Journal of Cheminformatics, Numer 16, 2024, ISSN 1758-2946
Wydawca: Chemistry Central
DOI: 10.1186/s13321-024-00924-y

Cross modality learning of cell painting and transcriptomics data improves mechanism of action clustering and bioactivity modelling

Autorzy: Son V. Ha, Steffen Jaensch, Maciej M. Kańduła, Dorota Herman, Paul Czodrowski, Hugo Ceulemans
Opublikowane w: Scientific Reports, Numer 15, 2025, ISSN 2045-2322
Wydawca: Nature Publishing Group
DOI: 10.1038/s41598-025-05914-0

PILOT: equivariant diffusion for pocket-conditioned <i>de novo</i> ligand generation with multi-objective guidance <i>via</i> importance sampling

Autorzy: Julian Cremer, Tuan Le, Frank Noé, Djork-Arné Clevert, Kristof T. Schütt
Opublikowane w: Chemical Science, Numer 15, 2024, Strona(/y) 14954-14967, ISSN 2041-6520
Wydawca: Royal Society of Chemistry
DOI: 10.1039/d4sc03523b

Synergies between Quantum Mechanics and Machine Learning for Advancing Pharmaceutical Research

Autorzy: Alessio Fallani
Opublikowane w: PhD dissertation, 2024
Wydawca: University of Luxembourg Open Repository and Bibliography

Development of small molecule inhibitors of protein nucleic acid interactions with the use of computer-aided drug discovery tools

Autorzy: Mariia Radaeva
Opublikowane w: Doctoral Thesis, 2024
Wydawca: University of British Columbia Library
DOI: 10.14288/1.0445334

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

Autorzy: Peter Bart Rudolf Hartog
Opublikowane w: Doctoral thesis, 2025
Wydawca: TUM School of Life Sciences

Prediction of yields of chemical reactions

Autorzy: Varvara Voinarovska
Opublikowane w: Doctoral thesis, 2024
Wydawca: TUM School of Natural Sciences

Equivariant graph neural networks in drug discover: from property prediction to molecule generation

Autorzy: Julian Cremer
Opublikowane w: PhD dissertation, 2024, Strona(/y) 147
Wydawca: Universitat Pompeu Fabra

Computer-aided synthesis planning for real-world applications

Autorzy: Paula Torren Peraire
Opublikowane w: Doctoral thesis, 2025
Wydawca: TUM School of Natural Sciences

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

Autorzy: Alan Kai Hassen, Paula Torren-Peraire, Samuel Genheden, Jonas Verhoeven, Mike Preuss, Igor V. Tetko
Opublikowane w: NeurIPS 2022 Workshop AI4Science, 2022
Wydawca: OpenReview.net

Robust Task-Specific Adaption of Models for Drug-Target Interaction Prediction

Autorzy: Svensson, E., Hoedt, P.-J., Hochreiter, S., Klambauer, G.
Opublikowane w: 36th Conference on Neural Information Processing Systems (NeurIPS 2022), 2022
Wydawca: NeurIPS 2022
DOI: 10.5281/zenodo.8138500

Atom-Level Optical Chemical Structure Recognition with Limited Supervision

Autorzy: Martijn Oldenhof, Edward De Brouwer, Adam Arany, Yves Moreau
Opublikowane w: 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024, Strona(/y) 17669-17678
Wydawca: IEEE
DOI: 10.1109/cvpr52733.2024.01673

Multi-Modal Representation learning for molecules

Autorzy: Muhammad Arslan Masood, Markus Heinonen, Samuel Kaski
Opublikowane w: ICLR 2025 Workshop LMRL, 2025
Wydawca: OpenReview.net
DOI: 10.5281/zenodo.15484224

Leveraging expert feedback to align proxy and ground truth rewards in goal-oriented molecular generation

Autorzy: Julien Martinelli, Yasmine Nahal, Duong Lê, Ola Engkvist, Samuel Kaski
Opublikowane w: NeurIPS 2023 AI for Drug Discovery and Development (AI4D3) workshop, 2023, Strona(/y) 1-16
Wydawca: NeurIPS

Navigating the Design Space of Equivariant Diffusion-Based Generative Models for De Novo 3D Molecule Generation

Autorzy: Tuan Le, Julian Cremer, Frank Noé, Djork-Arné Clevert, Kristof Schütt
Opublikowane w: ICLR 2024, 2024
Wydawca: arXiv
DOI: 10.48550/arxiv.2309.17296

Contrastive Learning of Image- and Structure-Based Representations in Drug Discovery

Autorzy: Sanchez-Fernandez, A., Rumetshofer, E., Hochreiter, S., Klambauer, G.
Opublikowane w: International Conference on Learning Representations, 2022
Wydawca: MLDD workshop, ICLR 2022
DOI: 10.5281/zenodo.8137823

MC-LSTM: Mass-Conserving LSTM

Autorzy: Hoedt, PJ., Kratzert, F., Klotz, D., Halmich, C., Holzleitner, M., Nearing, G., Hochreiter, S., Klambauer, G.
Opublikowane w: INTERNATIONAL CONFERENCE ON MACHINE LEARNING, 2021, ISSN 2640-3498
Wydawca: Cambridge MA: JMLR
DOI: 10.5281/zenodo.8138359

Expressive Graph Informer Networks

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

Synthesis Planning in Reaction Space: A Study on Success, Robustness and Diversity

Autorzy: Alan Kai Hassen, Helen Lai, Samuel Genheden, Mike Preuss, Djork-Arné Clevert
Opublikowane w: ChemRxiv Preprint, 2025
Wydawca: ChemRxiv
DOI: 10.26434/chemrxiv-2025-js7dt

A reagent-driven visual method for analyzing chemical reaction data

Autorzy: Mikhail Andronov, Natalia Andronova, Michael Wand, Jürgen Schmidhuber, Djork-Arné Clevert
Opublikowane w: arXiv preprint, 2024
Wydawca: ChemRxiv
DOI: 10.26434/chemrxiv-2024-q9tc4

Fast and scalable retrosynthetic planning with a transformer neural network and speculative beam search

Autorzy: Mikhail Andronov, Natalia Andronova, Michael Wand, Jürgen Schmidhuber, Djork-Arné Clevert
Opublikowane w: arXiv preprint, 2025
Wydawca: arXiv
DOI: 10.48550/arxiv.2508.01459

Modeling Non-Covalent Interatomic Interactions on a Photonic Quantum Computer

Autorzy: Sarkis, M., Fallani, A.,Tkatchenko, A.
Opublikowane w: 2023
Wydawca: arXiv
DOI: 10.48550/arxiv.2306.08544

Which modern AI methods provide accurate predictions of toxicological endpoints? Analysis of Tox24 challenge results.

Autorzy: Stephanie A. Eytcheson, Igor V. Tetko
Opublikowane w: 2025
Wydawca: ChemRxiv
DOI: 10.26434/chemrxiv-2025-7k7x3

NETWORK ANALYSIS OF THE ORGANIC CHEMISTRY IN PATENTS, LITERATURE, AND PHARMACEUTICAL INDUSTRY

Autorzy: Thierry Kogej, Emma Svensson, Emma Rydholm, Tomas Bastys, Christos Kannas, Mikhail Kabeshov, Samuel Genheden, Ola Engkvist
Opublikowane w: Chemrxiv, Numer Chemrxiv, 2024
Wydawca: ChemRxiv
DOI: 10.26434/chemrxiv-2024-h4qlt

openOCHEM consensus model wins Kaggle First EUOS/SLAS Joint Compound Solubility Challenge

Autorzy: Kopp, A., Hartog, P., Šícho, M., Godin, G., Tetko, I.V.
Opublikowane w: 2023
Wydawca: ChemRxiv
DOI: 10.26434/chemrxiv-2023-p8qcv

Equivariant Graph Neural Networks for Toxicity Prediction

Autorzy: Cremer, J., Medrano Sandonas, L., Tkatchenko, A., Clevert, D.A., De Fabritiis, G.
Opublikowane w: 2023, ISSN 2573-2293
Wydawca: ChemRxiv
DOI: 10.26434/chemrxiv-2023-9kb55

Temporal Evaluation of Probability Calibration with Experimental Errors

Autorzy: Hannah Rosa Friesacher, Emma Svensson, Adam Arany, Lewis Mervin, Ola Engkvist
Opublikowane w: Lecture Notes in Computer Science, AI in Drug Discovery, 2024, Strona(/y) 13-20
Wydawca: Springer Nature Switzerland
DOI: 10.1007/978-3-031-72381-0_2

Latent-Conditioned Equivariant Diffusion for Structure-Based De Novo Ligand Generation

Autorzy: Julian Cremer, Tuan Le, Djork-Arné Clevert, Kristof T. Schütt
Opublikowane w: Lecture Notes in Computer Science, AI in Drug Discovery, 2024, Strona(/y) 36-46
Wydawca: 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

Autorzy: Alessio Fallani, José Arjona-Medina, Konstantin Chernichenko, Ramil Nugmanov, Jörg Kurt Wegner, Alexandre Tkatchenko
Opublikowane w: Lecture Notes in Computer Science, AI in Drug Discovery, 2024, Strona(/y) 71-81
Wydawca: 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

Autorzy: Yasmine Nahal, Markus Heinonen, Mikhail Kabeshov, Jon Paul Janet, Eva Nittinger, Ola Engkvist, Samuel Kaski
Opublikowane w: Lecture Notes in Computer Science, AI in Drug Discovery, 2024, Strona(/y) 58-70
Wydawca: Springer Nature Switzerland
DOI: 10.1007/978-3-031-72381-0_6

Balancing Imbalanced Toxicity Models: Using MolBERT with Focal Loss

Autorzy: Muhammad Arslan Masood, Samuel Kaski, Hugo Ceulemans, Dorota Herman, Markus Heinonen
Opublikowane w: Lecture Notes in Computer Science, AI in Drug Discovery, 2024, Strona(/y) 82-97
Wydawca: Springer Nature Switzerland
DOI: 10.1007/978-3-031-72381-0_8

Curating Reagents in Chemical Reaction Data with an Interactive Reagent Space Map

Autorzy: Mikhail Andronov, Natalia Andronova, Michael Wand, Jürgen Schmidhuber, Djork-Arné Clevert
Opublikowane w: Lecture Notes in Computer Science, AI in Drug Discovery, 2024, Strona(/y) 21-35
Wydawca: Springer Nature Switzerland
DOI: 10.1007/978-3-031-72381-0_3

Temporal Evaluation of Uncertainty Quantification Under Distribution Shift

Autorzy: Emma Svensson, Hannah Rosa Friesacher, Adam Arany, Lewis Mervin, Ola Engkvist
Opublikowane w: Lecture Notes in Computer Science, AI in Drug Discovery, 2024, Strona(/y) 132-148
Wydawca: 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

Autorzy: Mathias Hilfiker, Leonardo Medrano Sandonas, Marco Klähn, Ola Engkvist, Alexandre Tkatchenko
Opublikowane w: Lecture Notes in Computer Science, AI in Drug Discovery, 2024, Strona(/y) 47-57
Wydawca: Springer Nature Switzerland
DOI: 10.1007/978-3-031-72381-0_5

Registries in Machine Learning-Based Drug Discovery: A Shortcut to Code Reuse

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

Deep Bayesian Experimental Design for Drug Discovery

Autorzy: Muhammad Arslan Masood, Tianyu Cui, Samuel Kaski
Opublikowane w: Lecture Notes in Computer Science, AI in Drug Discovery, 2024, Strona(/y) 149-159
Wydawca: Springer Nature Switzerland
DOI: 10.1007/978-3-031-72381-0_12

Introduction to the Special Issue: AI Meets Toxicology

Autorzy: Günter Klambauer, Djork-Arné Clevert, Imran Shah, Emilio Benfenati, Igor V. Tetko
Opublikowane w: Chemical Research in Toxicology, Numer 36, 2023, Strona(/y) 1163-1167, ISSN 0893-228X
Wydawca: American Chemical Society
DOI: 10.1021/acs.chemrestox.3c00217

Tox24 Challenge

Autorzy: Igor V. Tetko
Opublikowane w: Chemical Research in Toxicology, Numer 37, 2024, Strona(/y) 825-826, ISSN 0893-228X
Wydawca: American Chemical Society
DOI: 10.1021/acs.chemrestox.4c00192

Which Modern AI Methods Provide Accurate Predictions of Toxicological End Points? Analysis of Tox24 Challenge Results

Autorzy: Stephanie A. Eytcheson, Igor V. Tetko
Opublikowane w: Chemical Research in Toxicology, 2025, ISSN 0893-228X
Wydawca: American Chemical Society
DOI: 10.1021/acs.chemrestox.5c00273

Advanced machine learning for innovative drug discovery

Autorzy: Igor V. Tetko, Djork-Arné Clevert
Opublikowane w: Journal of Cheminformatics, Numer 17, 2025, ISSN 1758-2946
Wydawca: Chemistry Central
DOI: 10.1186/s13321-025-01061-w

S-07-03 A snapshot of AI in predictive toxicology: explainable AI

Autorzy: I.V. Tetko
Opublikowane w: Toxicology Letters, Numer 368, 2022, Strona(/y) S25-S26, ISSN 0378-4274
Wydawca: Elsevier BV
DOI: 10.1016/j.toxlet.2022.07.085

S02-04 Computational Toxicology in Drug Safety

Autorzy: I. Tetko
Opublikowane w: Toxicology Letters, Numer 399, 2024, Strona(/y) S14, ISSN 0378-4274
Wydawca: Elsevier BV
DOI: 10.1016/j.toxlet.2024.07.047

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