Dr. Igor Tetko received his MSc from the Moscow Institute of Physics and Technology (summa cum laude - red diploma), one of the top-ranked Universities in the Soviet Union. He carried out his postdoctoral studies in neuroinformatics at the University of Lausanne, where he developed algorithms for the analysis of EEG data, synfire chains and theoretical modeling of thalamo-cortical organization of the brain. Since 2001, Dr. Tetko is a group leader in Chemical Informatics at Helmholtz Zentrum München, as well as CEO of BigChem GmbH. Dr. Tetko has co-authored >200 publications in chemoinformatics, bioinformatics, neuroinformatics and machine learning https://scholar.google.com/citations?user=eMe8DOkAAAAJ. He is a General Chair of the International Conference on Artificial Neural Networks (https://icann2024.org). He currently coordinates two Horizon Marie Skłodowska-Curie Innovative Training Network European Industrial Doctorates projects: Advanced machine learning for Innovative Drug Discovery (AIDD) (https://ai-dd.eu) and Explainable AI for Molecules - AiChemist (https://aichemist.eu) and has coordinated two other such projects in the past. He is also an Associate Editor of the ACS ChemResTox (https://pubs.acs.org/journal/crtoec) journal and a guest editor of J. Cheminformatics (https://www.biomedcentral.com/collections/AIDR).
OpenTox Summer School 2024
OCHEM - platform for winning Challenges
After a brief overview to OCHEM platform (https://ochem.eu) and its open-source version (https://github.com/openochem) I will discuss some success stories using the OCHEM platform for the US EPA ToxCast Challenge http://web.archive.org/web/20150616141428/http://www.epa.gov/ncct/challenges.html [1], the Tox21 Challenge https://tripod.nih.gov/tox21/challenge [2] and the 1st Joint EUOS/SLAS Kaggle Challenge https://www.kaggle.com/competitions/euos-slas [3]. I will demonstrate the typical steps and strategies that were used for each of these challenges. A full modelling exercise for reproducing the winning model in the US EPA ToxCast Challenge will be shown. Participants will also be given an introduction to the Tox24 Challenge https://e-nns.org/icann2024/challenge [4] and will be invited to test their knowledge by developing and contributing models to the Challenge.
- Novotarskyi, S.; Abdelaziz, A.; Sushko, Y.; Körner, R.; Vogt, J.; Tetko, I. V. ToxCast EPA in Vitro to in Vivo Challenge: Insight into the Rank-I Model. Chem. Res. Toxicol. 2016, 29 (5), 768–775. https://doi.org/10.1021/acs.chemrestox.5b00481
- Abdelaziz, A.; Spahn-Langguth, H.; Schramm, K.-W.; Tetko, I. V. Consensus Modeling for HTS Assays Using In Silico Descriptors Calculates the Best Balanced Accuracy in Tox21 Challenge. Front. Environ. Sci. 2016, 4. https://doi.org/10.3389/fenvs.2016.00002
- Hunklinger, A.; Hartog, P.; Šícho, M.; Godin, G.; Tetko, I. V. The openOCHEM Consensus Model Is the Best-Performing Open-Source Predictive Model in the First EUOS/SLAS Joint Compound Solubility Challenge. SLAS Discov. 2024, 29 (2), 100144. https://doi.org/10.1016/j.slasd.2024.01.005
- Tetko, I. V. Tox24 Challenge. Chem. Res. Toxicol. 2024, 37 (6), 825–826. https://doi.org/10.1021/acs.chemrestox.4c00192.