Explainable AI for Molecules - AiChemist

Project Information

AiChemist

Grant agreement ID: 101120466

DOI

10.3030/101120466

EC signature date 14 July 2023

Start date 1 September 2023

End date 31 August 2027

Funded under

• Marie Skłodowska-Curie Actions (MSCA)

Total cost

No data

EU contribution

€ 3 028 356,00

Coordinated by

HELMHOLTZ ZENTRUM MUENCHEN DEUTSCHES FORSCHUNGSZENTRUM FUER GESUNDHEIT UND UMWELT GMBH
Germany

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 .

Publications

Peer reviewed articles (5)

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

Author(s): Peter B. R. Hartog, Fabian Krüger, Samuel Genheden, Igor V. Tetko
Published in: Journal of Cheminformatics, Issue 16, 2024, ISSN 1758-2946
Publisher: Springer Science and Business Media LLC
DOI: 10.1186/S13321-024-00824-1

NanoToxRadar: A Multitarget Nano-QSAR Model for Predicting the Cytotoxicity Values of Multicomponent Nanoparticles

Author(s): Jaehyeon Park, Shahzad Rashid, Helena Copsey, Lang Tran, Alex Zabeo, Danail Hristozov, Giorgos P. Gakis, Costas Charitidis, Seokjoo Yoon, Hyun Kil Shin
Published in: ACS Nanoscience Au, Issue 5, 2025, ISSN 2694-2496
Publisher: American Chemical Society (ACS)
DOI: 10.1021/ACSNANOSCIENCEAU.5C00035

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

Author(s): Andrea Hunklinger, Peter Hartog, Martin Šícho, Guillaume Godin, Igor V. Tetko
Published in: SLAS Discovery, Issue 29, 2024, ISSN 2472-5552
Publisher: Elsevier BV
DOI: 10.26434/CHEMRXIV-2023-P8QCV

Predicting reaction conditions: a data-driven perspective

Author(s): Matthew Ball, Dragos Horvath, Thierry Kogej, Mikhail Kabeshov, Alexandre Varnek
Published in: Chemical Science, Issue 16, 2025, ISSN 2041-6520
Publisher: Royal Society of Chemistry (RSC)
DOI: 10.26434/CHEMRXIV-2025-VC6TV

MolEncoder: towards optimal masked language modeling for molecules

Author(s): Fabian P. Krüger, Nicklas Österbacka, Mikhail Kabeshov, Ola Engkvist, Igor Tetko
Published in: Digital Discovery, 2025, ISSN 2635-098X
Publisher: Royal Society of Chemistry (RSC)
DOI: 10.1039/D5DD00369E

Other (3)

Tox24 Challenge

Author(s): Tetko, Igor V.
Published in: Chemical Research in Toxicology, 2024
DOI: 10.1021/ACS.CHEMRESTOX.4C00192

Advanced machine learning for innovative drug discovery

Author(s): Igor V. Tetko; Djork-Arné Clevert
Published in: Journal of Cheminformatics, 2025
DOI: 10.1186/S13321-025-01061-W

Advancing Human and Environmental Safety Science Using <i>In Silico</i> Methods

Author(s): Alessandra Roncaglioni, Simona Kovarich, Kamel Mansouri, Igor V. Tetko
Published in: Chemical Research in Toxicology, Issue 38, 2025, ISSN 0893-228X
Publisher: American Chemical Society (ACS)
DOI: 10.1021/ACS.CHEMRESTOX.5C00293

Conference proceedings (2)

Uni-Mol Docking V2: Towards Realistic and Accurate Binding Pose Prediction

Author(s): Eric Alcaide, Zhifeng Gao, Guolin Ke, Yaqi Li, Linfeng Zhang, Hang Zheng, Gengmo Zhou
Published in: Lecture Notes in Computer Science, Artificial Neural Networks and Machine Learning. ICANN 2025 International Workshops and Special Sessions, 2025
Publisher: Springer Nature Switzerland
DOI: 10.48550/ARXIV.2405.11769

MolEncoder: Improved Masked Language Modeling for Molecules

Author(s): Fabian P. Krüger, Nicklas Österbacka, Mikhail Kabeshov, Ola Engkvist, Igor Tetko
Published in: Lecture Notes in Computer Science, Artificial Neural Networks and Machine Learning. ICANN 2025 International Workshops and Special Sessions, 2025
Publisher: Springer Nature Switzerland
DOI: 10.26434/CHEMRXIV-2025-H4W9D