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Orsi, Markus; Probst, Daniel; Schwaller, Philippe; Reymond, Jean-Louis (2023). Alchemical analysis of FDA approved drugs. Digital discovery, 2(5), pp. 1289-1296. Royal Society of Chemistry 10.1039/d3dd00039g
Probst, Daniel; Schwaller, Philippe; Reymond, Jean-Louis (2022). Reaction classification and yield prediction using the differential reaction fingerprint DRFP. Digital discovery, 1(2), pp. 91-97. Royal Society of Chemistry 10.1039/d1dd00006c
Schwaller, Philippe; Probst, Daniel; Vaucher, Alain C.; Nair, Vishnu H.; Kreutter, David Patrick Joseph; Laino, Teodoro; Reymond, Jean-Louis (2021). Mapping the space of chemical reactions using attention-based neural networks. Nature machine intelligence, 3(2), pp. 144-152. Springer Nature 10.1038/s42256-020-00284-w
Stoklosa, Paulina; Probst, Daniel; Reymond, Jean-Louis; Peinelt, Christine (2020). The name tells the story: Two-pore channels. Cell calcium, 89, p. 102215. Elsevier 10.1016/j.ceca.2020.102215
Capecchi, Alice; Probst, Daniel; Reymond, Jean-Louis (2020). One molecular fingerprint to rule them all: drugs, biomolecules, and the metabolome. Journal of cheminformatics, 12(1) Springer 10.1186/s13321-020-00445-4
Probst, Daniel; Reymond, Jean-Louis (2020). Visualization of very large high-dimensional data sets as minimum spanning trees. Journal of cheminformatics, 12(1) Springer 10.1186/s13321-020-0416-x
Arús-Pous, Josep; Awale, Mahendra; Probst, Daniel; Reymond, Jean-Louis (2019). Exploring Chemical Space with Machine Learning. CHIMIA, 73(12), pp. 1018-1023. Schweizerische Chemische Gesellschaft 10.2533/chimia.2019.1018
Delalande, Clémence; Awale, Mahendra; Rubin, Matthias; Probst, Daniel; Ozhathil, Lijo C.; Gertsch, Jürg; Abriel, Hugues; Reymond, Jean-Louis (2019). Optimizing TRPM4 inhibitors in the MHFP6 chemical space. European journal of medicinal chemistry, 166, pp. 167-177. Elsevier 10.1016/j.ejmech.2019.01.048
Capecchi, Alice; Awale, Mahendra; Probst, Daniel; Reymond, Jean-Louis (2019). PubChem and ChEMBL beyond Lipinski. Molecular informatics, 38(5), p. 1900016. Wiley 10.1002/minf.201900016
Capecchi, Alice; Awale, Mahendra; Probst, Daniel; Reymond, Jean-Louis (2018). Beyond Lipinski – an analysis of the PubChem chemical space (Unpublished). In: Summer School on Machine Learning in Drug Design. Leuven, Belgium. Monday, August 20, 2018 - to Wednesday, August 22, 2018.
Schwaller, Philippe; Probst, Daniel; Vaucher, Alain C.; Nair, Vishnu H; Laino, Teodoro; Reymond, Jean-Louis (26 December 2019). Data-Driven Chemical Reaction Classification, Fingerprinting and Clustering using Attention-Based Neural Networks ChemRxiv 10.26434/chemrxiv.9897365.v2
