| Enumeration of 166 billion organic small molecules in the chemical universe database GDB-17 L Ruddigkeit, R Van Deursen, LC Blum, JL Reymond Journal of chemical information and modeling 52 (11), 2864-2875, 2012 | 1646 | 2012 |
| An efficient one-step site-directed and site-saturation mutagenesis protocol L Zheng, U Baumann, JL Reymond Nucleic acids research 32 (14), e115-e115, 2004 | 1461 | 2004 |
| 970 million druglike small molecules for virtual screening in the chemical universe database GDB-13 LC Blum, JL Reymond Journal of the American Chemical Society 131 (25), 8732-8733, 2009 | 956 | 2009 |
| The chemical space project JL Reymond Accounts of chemical research 48 (3), 722-730, 2015 | 665 | 2015 |
| Multivalent glycoconjugates as anti-pathogenic agents A Bernardi, J Jiménez-Barbero, A Casnati, C De Castro, T Darbre, ... Chemical Society Reviews 42 (11), 4709-4727, 2013 | 592 | 2013 |
| Virtual exploration of the chemical universe up to 11 atoms of C, N, O, F: assembly of 26.4 million structures (110.9 million stereoisomers) and analysis for new ring systems … T Fink, JL Reymond Journal of chemical information and modeling 47 (2), 342-353, 2007 | 540 | 2007 |
| Virtual exploration of the small‐molecule chemical universe below 160 daltons T Fink, H Bruggesser, JL Reymond Angewandte Chemie International Edition 44 (10), 1504-1508, 2005 | 444 | 2005 |
| Chemical space as a source for new drugs JL Reymond, R Van Deursen, LC Blum, L Ruddigkeit MedChemComm 1 (1), 30-38, 2010 | 388 | 2010 |
| One molecular fingerprint to rule them all: drugs, biomolecules, and the metabolome A Capecchi, D Probst, JL Reymond Journal of cheminformatics 12, 1-15, 2020 | 356 | 2020 |
| Exploring chemical space for drug discovery using the chemical universe database JL Reymond, M Awale ACS chemical neuroscience 3 (9), 649-657, 2012 | 354 | 2012 |
| Enzyme assays for high-throughput screening JP Goddard, JL Reymond Current opinion in biotechnology 15 (4), 314-322, 2004 | 329 | 2004 |
| Randomized SMILES strings improve the quality of molecular generative models J Arús-Pous, SV Johansson, O Prykhodko, EJ Bjerrum, C Tyrchan, ... Journal of cheminformatics 11, 1-13, 2019 | 326 | 2019 |
| Prediction of chemical reaction yields using deep learning P Schwaller, AC Vaucher, T Laino, JL Reymond Machine learning: science and technology 2 (1), 015016, 2021 | 301 | 2021 |
| AiZynthFinder: a fast, robust and flexible open-source software for retrosynthetic planning S Genheden, A Thakkar, V Chadimová, JL Reymond, O Engkvist, ... Journal of cheminformatics 12 (1), 70, 2020 | 298 | 2020 |
| Inhibition and dispersion of Pseudomonas aeruginosa biofilms by glycopeptide dendrimers targeting the fucose-specific lectin LecB EMV Johansson, SA Crusz, E Kolomiets, L Buts, RU Kadam, M Cacciarini, ... Chemistry & biology 15 (12), 1249-1257, 2008 | 291 | 2008 |
| Novel methods for biocatalyst screening D Wahler, JL Reymond Current opinion in chemical biology 5 (2), 152-158, 2001 | 282 | 2001 |
| Mapping the space of chemical reactions using attention-based neural networks P Schwaller, D Probst, AC Vaucher, VH Nair, D Kreutter, T Laino, ... Nature machine intelligence 3 (2), 144-152, 2021 | 279 | 2021 |
| Visualization of very large high-dimensional data sets as minimum spanning trees D Probst, JL Reymond Journal of Cheminformatics 12 (1), 12, 2020 | 278 | 2020 |
| Peptide dendrimers as artificial enzymes, receptors, and drug-delivery agents T Darbre, JL Reymond Accounts of chemical research 39 (12), 925-934, 2006 | 278 | 2006 |
| Recent advances in enzyme assays JP Goddard, JL Reymond TRENDS in Biotechnology 22 (7), 363-370, 2004 | 259 | 2004 |
Daniel ProbstWURPatvirtintas el. paštas wur.nl