Noé Sturm

Novartis (Switzerland) — Switzerland

Computer Science · Physical Sciences

12h-index831citations39works8.02yr avg
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Research Topics

Computational Drug Discovery Methods(33), Machine Learning in Materials Science(9), Microbial Natural Products and Biosynthesis(7), Machine Learning and Algorithms(7), Advanced Graph Neural Networks(6)

Publications39 total

Machine learning proteochemometric models for Cereblon glue activity predictions
Artificial Intelligence in the Life Sciences·2024· 8 citedOpen Access
Prediction of Small-Molecule Developability Using Large-Scale <i>In Silico</i> ADMET Models
Journal of Medicinal Chemistry·2023· 19 cited
MELLODDY: Cross-pharma Federated Learning at Unprecedented Scale Unlocks Benefits in QSAR without Compromising Proprietary Information
Journal of Chemical Information and Modeling·2023· 94 citedOpen Access
Industry-Scale Orchestrated Federated Learning for Drug Discovery
Proceedings of the AAAI Conference on Artificial Intelligence·2023· 37 citedOpen Access
Conformal efficiency as a metric for comparative model assessment befitting federated learning
Artificial Intelligence in the Life Sciences·2023· 5 citedOpen Access
Industry-Scale Orchestrated Federated Learning for Drug Discovery
arXiv (Cornell University)·2022· 10 citedOpen Access
MELLODDY: cross pharma federated learning at unprecedented scale unlocks benefits in QSAR without compromising proprietary information
2022· 24 citedOpen Access
Conformal efficiency as a metric for comparative model assessment befitting federated learning
2022· 4 citedOpen Access
Splitting chemical structure data sets for federated privacy-preserving machine learning
Journal of Cheminformatics·2021· 57 citedOpen Access
Don’t Overweight Weights: Evaluation of Weighting Strategies for Multi-Task Bioactivity Classification Models
Molecules·2021· 10 citedOpen Access
Splitting chemical structure data sets for federated privacy-preserving machine learning
2021· 2 citedOpen Access
Splitting chemical structure data sets for federated privacy-preserving machine learning
2021Open Access
Don’t overweight weights: Evaluation of weighting strategies for multi-task bioactivity classification models
2021Open Access
Don’t overweight weights: Evaluation of weighting strategies for multi-task bioactivity classification models
2021Open Access
Splitting chemical structure data sets for federated privacy-preserving machine learning
2021· 1 citedOpen Access
Splitting chemical structure data sets for federated privacy-preserving machine learning
2021· 3 citedOpen Access
Splitting chemical structure data sets for federated privacy-preserving machine learning
2021· 4 citedOpen Access
Splitting chemical structure data sets for federated privacy-preserving machine learning
2021Open Access
Comparison of Chemical Structure and Cell Morphology Information for Multitask Bioactivity Predictions
Journal of Chemical Information and Modeling·2021· 48 cited
Multitask Bioactivity Predictions Using Structural Chemical and Cell Morphology Information
2020· 2 citedOpen Access
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Frequent Co-authors

Ola Engkvist(19), Adam Zalewski(16), Wouter Heyndrickx(15), Lina Humbeck(14), Jaak Simm(13), Yves Moreau(13), Hongming Chen(12), Bernd Beck(12), Ansgar Schuffenhauer(12), Hugo Ceulemans(10), Lewis Mervin(9), Yves Vandriessche(7), Günter Klambauer(7), Lukas Friedrich(6), Martijn Oldenhof(6), Peter Schmidtke(6), Ádám Arany(6), Andreas Mayr(6), Tobias Morawietz(5), Simon Harnqvist(5)