| Enabling late-stage drug diversification by high-throughput experimentation with geometric deep learning DF Nippa, K Atz, R Hohler, AT Müller, A Marx, C Bartelmus, G Wuitschik, ... Nature Chemistry 16 (2), 239-248, 2024 | 24 | 2024 |
| Late-stage functionalization and its impact on modern drug discovery: medicinal chemistry and chemical biology highlights DF Nippa, R Hohler, AF Stepan, U Grether, DB Konrad, RE Martin Chimia 76 (3), 258-260, 2022 | 12 | 2022 |
| Prospective de novo drug design with deep interactome learning K Atz, L Cotos, C Isert, M Håkansson, D Focht, M Hilleke, DF Nippa, M Iff, ... Nature Communications 15 (1), 3408, 2024 | 6* | 2024 |
| Identifying opportunities for late-stage CH alkylation with high-throughput experimentation and in silico reaction screening DF Nippa, K Atz, AT Müller, J Wolfard, C Isert, M Binder, O Scheidegger, ... Communications Chemistry 6 (1), 256, 2023 | 5* | 2023 |
| Simple User-Friendly Reaction Format DF Nippa, AT Müller, K Atz, DB Konrad, U Grether, RE Martin, ... | 1 | 2024 |
| Heterocyclic compounds M AMOUSSA, J Benz, NK BRIAN, K FRISTON, M GIROUD, U Grether, ... US Patent App. 18/490,967, 2024 | | 2024 |
| Improving compound synthesis efficiency through laboratory automation and artificial intelligence DF Nippa Ludwig-Maximilians-Universität München, 2024 | | 2024 |
| Geometric deep learning-guided Suzuki reaction conditions assessment for applications in medicinal chemistry K Atz, DF Nippa, AT Müller, V Jost, A Anelli, M Reutlinger, C Kramer, ... RSC Medicinal Chemistry 15 (7), 2310-2321, 2024 | | 2024 |
Uwe GretherF. Hoffmann-La Roche Ltd在 roche.com 的电子邮件经过验证
