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Daniel Probst

Assistant Professor

Wageningen University & Research

Netherlands

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About

Dr. Daniel Probst is an Assistant Professor at EPFL - École Polytechnique Fédérale de Lausanne in Switzerland. His research focuses on deep learning applications in chemistry, particularly in enzyme-catalyzed reactions and drug analysis. Recent contributions include works on machine learning in chemical processes, explainability frameworks for deep learning, and the societal impact of diversity and inclusivity in the field.

Articles (9)

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2025

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2025

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2025

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2023

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2023

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2023

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2023

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2023

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2023

Collaborators (4)

Alan Bridge

SIB Swiss Institute of Bioinformatics

SWITZERLAND

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Justin van der Hooft

Wageningen University & Research

NETHERLANDS

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Adriano Rutz

ETH Zürich

SWITZERLAND

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Thomas Weymuth

Senior Scientist

ETH Zürich

SWITZERLAND

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Daniel Probst

Research Interests

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Articles (9)

MITE: the Minimum Information about a Tailoring Enzyme database for capturing specialized metabolite biosynthesis.

Commit: Reaction classification and yield prediction using the differential reaction fingerprint DRFP

Learning on compressed molecular representations

Alchemical analysis of FDA approved drugs

Aiming beyond slight increases in accuracy

The Societal and Scientific Importance of Inclusivity, Diversity, and Equity in Machine Learning for Chemistry

An explainability framework for deep learning on chemical reactions exemplified by enzyme-catalysed reaction classification

Quantum chemical data generation as fill-in for reliability enhancement of machine-learning reaction and retrosynthesis planning

EnzymeMap: Curation, validation and data-driven prediction of enzymatic reactions

Collaborators (4)

Alan Bridge

Justin van der Hooft

Adriano Rutz

Thomas Weymuth

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