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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 Beyond Lipinski – an analysis of the PubChem chemical space (Unpublished).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.
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
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
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
Probst, Daniel; Reymond, Jean-Louis (2018). A probabilistic molecular fingerprint for big data settings. Journal of cheminformatics, 10(1) BioMed Central 10.1186/s13321-018-0321-8
Probst, Daniel; Reymond, Jean-Louis (2018). Exploring DrugBank in Virtual Reality Chemical Space. Journal of chemical information and modeling, 58(9), pp. 1731-1735. American Chemical Society 10.1021/acs.jcim.8b00402
Probst, Daniel; Reymond, Jean-Louis (2018). FUn: A Framework for Interactive Visualizations of Large, High Dimensional Datasets on the Web. Bioinformatics, 34(8), pp. 1433-1435. Oxford University Press 10.1093/bioinformatics/btx760
Probst, Daniel; Reymond, Jean-Louis (2018). SmilesDrawer: Parsing and Drawing SMILES-Encoded Molecular Structures Using Client-Side JavaScript. Journal of chemical information and modeling, 58(1), pp. 1-7. American Chemical Society 10.1021/acs.jcim.7b00425
Arús-Pous, Josep; Probst, Daniel; Reymond, Jean-Louis (2018). Deep Learning Invades Drug Design and Synthesis. CHIMIA, 72(1), pp. 70-71. Schweizerische Chemische Gesellschaft 10.2533/chimia.2018.70
Awale, Mahendra; Probst, Daniel; Reymond, Jean-Louis (2017). WebMolCS: A Web-Based Interface for Visualizing Molecules in Three-Dimensional Chemical Spaces. Journal of chemical information and modeling, 57(4), pp. 643-649. American Chemical Society 10.1021/acs.jcim.6b00690
Di Bonaventura, Ivan; Jin, Xian; Visini, Ricardo; Probst, Daniel; Javor, Sacha; Gan, Bee-Ha; Michaud, Gaëlle; Natalello, Antonino; Doglia, Silvia Maria; Köhler, Thilo; van Delden, Christian; Stocker, Achim; Darbre, Tamis; Reymond, Jean-Louis (2017). Chemical space guided discovery of antimicrobial bridged bicyclic peptides against Pseudomonas aeruginosa and its biofilms. Chemical Science, 8(10), pp. 6784-6798. The Royal Society of Chemistry 10.1039/C7SC01314K
He, Runze; Di Bonaventura, Ivan; Visini, Ricardo; Gan, Bee-Ha; Fu, Yongchun; Probst, Daniel; Lüscher, Alexandre; Köhler, Thilo; van Delden, Christian; Stocker, Achim; Hong, Wenjing; Darbre, Tamis; Reymond, Jean-Louis (2017). Design, crystal structure and atomic force microscopy study of thioether ligated d , l -cyclic antimicrobial peptides against multidrug resistant Pseudomonas aeruginosa. Chemical Science, 8(11), pp. 7464-7475. The Royal Society of Chemistry 10.1039/C7SC01599B
Probst, Daniel; Heitz, Marc; Poirier, Marion; Gan, Bee Ha; Delalande, Clémence Marie Sandrine; Reymond, Jean-Louis (2017). Frontiers in Medicinal Chemistry 2017 in Bern, Switzerland. ChemMedChem, 12(19), pp. 1645-1651. Wiley-VCH 10.1002/cmdc.201700306
Awale, Mahendra; Visini, Ricardo; Probst, Daniel; Arus Pous, Josep; Reymond, Jean-Louis (2017). Chemical Space: Big Data Challenge for Molecular Diversity. CHIMIA, 71(10), pp. 661-666. Schweizerische Chemische Gesellschaft 10.2533/chimia.2017.661
