ProbstLab

Computer Science × Natural Sciences

Find me on:  Bluesky,  GitHub,  Google Scholar, and  ORCID

2025

 Boosting Protein Graph Representations through Static-Dynamic Fusion
ICML (2025)
Pengkang Guo, Bruno Correia, Pierre Vandergheynst, Daniel Probst
 MITE: the Minimum Information about a Tailoring Enzyme database for capturing specialized metabolite biosynthesis
Nucleic Acids Research (2025)
Adriano Rutz, Daniel Probst, Mitja M. Zdouc
 Generative Modeling of Full-Atom Protein Conformations using Latent Diffusion on Graph Embeddings
arXiv, accepted at NeurIPS 2025 (2025)
Aditya Sengar, Ali Hariri, Daniel Probst, Patrick Barth, Pierre Vandergheynst
 Commit: Reaction classification and yield prediction using the differential reaction fingerprint DRFP
Digital Discovery (2025)
Daniel Probst
 To Bin or not to Bin: Alternative Representations of Mass Spectra
arXiv, accepted at LMRL@ICLR 2025 (2025)
Niek de Jonge, Justin J. J. van der Hooft, Daniel Probst
 Implicit Neural Representations of Molecular Vector-Valued Functions
arXiv, accepted at LMRL@ICLR 2025 (2025)
Jirka Lhotka, Daniel Probst
 Learning on compressed molecular representations
Digital Discovery 4, 84-92 (2025)
Jan Weinreich, Daniel Probst

2024

 Language models can identify enzymatic active sites in protein sequences
Computational and Structural Biotechnology Journal 23, 1929–1937 (2024)
Yves Gaetan Nana Teukam, Loïc Kwate Dassi, Matteo Manica, Daniel Probst, Philippe Schwaller, Teodoro Laino
 Molecular set representation learning
Nature Machine Intelligence 6, 754–763 (2024)
Maria Boulougouri, Pierre Vandergheynst, Daniel Probst

2023

 EnzymeMap: curation, validation and data-driven prediction of enzymatic reactions
Chemical Science 14, 14229–14242 (2023)
Esther Heid, Daniel Probst,  William H. Green, Georg K. H. Madsen
 Quantum chemical data generation as fill-in for reliability enhancement of machine-learning reaction and retrosynthesis planning
Digital Discovery 2, 663–673 (2023)
Alessandra Taniato, Jan P. Unsleber, Alain C. Vaucher, Thomas Weymuth, Daniel Probst, Teodoro Laino, Markus Reiher
 An explainability framework for deep learning on chemical reactions exemplified by enzyme-catalysed reaction classification
Journal of Cheminformatics 15 (2023)
Daniel Probst
 Alchemical analysis of FDA approved drugs
Digital Discovery 2, 1289–1296 (2023)
Markus Orsi, Daniel Probst, Philippe Schwaller, Jean-Louis Reymond
 Aiming beyond slight increases in accuracy
Nature Reviews Chemistry 7, 227–228 (2023)
Daniel Probst

2022

 Biocatalysed synthesis planning using data-driven learning
Nature Communications 13 (2022)
Daniel Probst, Matteo Manica, Yves Gaetan Nana Teukam, Alessandro Castrogiovanni, Federico Paratore, Teodoro Laino
 Reaction classification and yield prediction using the differential reaction fingerprint DRFP
Digital Discovery 1, 91–97 (2022)
Daniel Probst, Philippe Schwaller, Jean-Louis Reymond

2021

 Mapping the space of chemical reactions using attention-based neural networks
Nature Machine Intelligence 3, 144–152 (2021)
Philippe Schwaller, Daniel Probst, Alain C. Vaucher, Vishnu H. Nair, David Kreutter, Teodoro Laino, Jean-Louis Reymond

2020

 One molecular fingerprint to rule them all: drugs, biomolecules, and the metabolome
Journal of Cheminformatics 12 (2020)
Alice Capecchi, Daniel Probst, Jean-Louis Reymond
 Time is of the essence: containment of the SARS-CoV-2 epidemic in Switzerland from February to May 2020
medRxiv (2020)
Christian L. Althaus, Daniel Probst, Anthony Hauser, Julien Riou
 The name tells the story: Two-pore channels
Cell Calcium 89, 102215 (2020)
Paulina Stokłosa, Daniel Probst, Jean-Louis Reymond, Christine Peinelt
 Visualization of very large high-dimensional data sets as minimum spanning trees
Journal of Cheminformatics 12 (2020)
Daniel Probst, Jean-Louis Reymond

2019

 Exploring Chemical Space with Machine Learning
CHIMIA 73, 1018 (2019)
Josep Arús-Pous, Mahendra Awale, Daniel Probst, Jean-Louis Reymond
 PubChem and ChEMBL beyond Lipinski
Molecular Informatics 38, 144–152 (2019)
Alice Capecchi, Mahendra Awale, Daniel Probst, Jean-Louis Reymond
 Optimizing TRPM4 inhibitors in the MHFP6 chemical space
European Journal of Medicinal Chemistry 166, 167–177 (2019)
Clémence Delalande, Mahendra Awale, Matthias Rubin, Daniel Probst, Lijo C. Ozhathil, Jürg Gertsch, Hugues Abriel, Jean-Louis Reymond

2018

 A probabilistic molecular fingerprint for big data settings
Journal of Cheminformatics 10, 144–152 (2018)
Daniel Probst, Jean-Louis Reymond
 Exploring DrugBank in Virtual Reality Chemical Space
Journal of Chemical Information and Modeling 58, 1731–1735 (2018)
Daniel Probst, Jean-Louis Reymond
 Deep Learning Invades Drug Design and Synthesis: Medical Chemistry and Chemical Biology Highlights
CHIMIA 72, 70 (2018)
Josep Arús-Pous, Daniel Probst, Jean-Louis Reymond
 SmilesDrawer: Parsing and Drawing SMILES-Encoded Molecular Structures Using Client-Side JavaScript
Journal of Chemical Information and Modeling 58, 1–7 (2018)
Daniel Probst, Jean-Louis Reymond

2017

 FUn: a framework for interactive visualizations of large, high-dimensional datasets on the web
Bioinformatics 34, 1433–1435 (2017)
Daniel Probst, Jean-Louis Reymond
 Chemical Space: Big Data Challenge for Molecular Diversity
CHIMIA 71, 0009-4293 (2017)
Mahendra Awale, Ricardo Visini, Daniel Probst, Josep Arús-Pous, Jean-Louis Reymond
 Design, crystal structure and atomic force microscopy study of thioether ligated D,L-cyclic antimicrobial peptides against multidrug resistant Pseudomonas aeruginosa
Chemical Science 8, 643–649 (2017)
Runze He, Ivan Di Bonaventura, Ricardo Visini, Bee-Ha Gan, Yongchun Fu, Daniel Probst, Alexandre Lüscher, Thilo Köhler, Christian van Delden, Achim Stocker,  Wenjing Hong,  Tamis Darbre, Jean-Louis Reymond
 Chemical space guided discovery of antimicrobial bridged bicyclic peptides against Pseudomonas aeruginosa and its biofilms
Chemical Science 8, 6784–6798 (2017)
Mahendra Awale, Ricardo Visini, Daniel Probst, Josep Arús-Pous, Jean-Louis Reymond
 WebMolCS: A Web-Based Interface for Visualizing Molecules in Three-Dimensional Chemical Spaces
Journal of Chemical Information and Modeling 57, 643–649 (2017)
Mahendra Awale, Daniel Probst, Jean-Louis Reymond