| Generative Recurrent Networks for De Novo Drug Design A Gupta, AT Müller, B Huisman, JA Fuchs, P Schneider, G Schneider Molecular Informatics 36, 2017 | 534 | 2017 |
| Recurrent Neural Network Model for Constructive Peptide Design AT Müller, JA Hiss, G Schneider Journal of Chemical Information and Modeling, 2018 | 218 | 2018 |
| modlAMP: Python for antimicrobial peptides AT Müller, G Gabernet, JA Hiss, G Schneider Bioinformatics 33 (17), 2753–2755, 2017 | 154 | 2017 |
| Designing anticancer peptides by constructive machine learning F Grisoni, CS Neuhaus, G Gabernet, AT Müller, JA Hiss, G Schneider ChemMedChem 13 (13), 1300-1302, 2018 | 98 | 2018 |
| Membranolytic anticancer peptides G Gabernet, AT Müller, JA Hiss, G Schneider MedChemComm 7 (12), 2232-2245, 2016 | 94 | 2016 |
| Hybrid network model for “deep learning” of chemical data: application to antimicrobial peptides P Schneider, AT Müller, G Gabernet, AL Button, G Posselt, S Wessler, ... Molecular informatics 36 (1-2), 1600011, 2017 | 54 | 2017 |
| In silico design and optimization of selective membranolytic anticancer peptides GS G Gabernet, D Gautschi, AT Müller, CS Neuhaus, L Armbrecht, PS Dittrich ... Scientific Reports, 2019 | 51 | 2019 |
| Rational Design of Membrane‐Pore‐Forming Peptides M Pillong, JA Hiss, P Schneider, YC Lin, G Posselt, B Pfeiffer, M Blatter, ... Small 13 (40), 1701316, 2017 | 33 | 2017 |
| 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, 1-10, 2023 | 32 | 2023 |
| Sparse Neural Network Models of Antimicrobial Peptide‐Activity Relationships AT Müller, AC Kaymaz, G Gabernet, G Posselt, S Wessler, JA Hiss, ... Molecular Informatics 35 (11-12), 606-614, 2016 | 24 | 2016 |
| Peptide–Membrane Interaction between Targeting and Lysis K Stutz, AT Müller, JA Hiss, P Schneider, M Blatter, B Pfeiffer, G Posselt, ... ACS Chemical Biology 12 (9), 2254-2259, 2017 | 14 | 2017 |
| Morphing of Amphipathic Helices to Explore the Activity and Selectivity of Membranolytic Antimicrobial Peptides AT Müller, G Posselt, G Gabernet, C Neuhaus, S Bachler, M Blatter, ... Biochemistry, 2020 | 6 | 2020 |
| Identifying opportunities for late-stage C-H alkylation with high-throughput experimentation and in silico reaction screening GS David F. Nippa, Kenneth Atz, Alex T. Müller, Jens Wolfard, Clemens Isert ... Communications Chemistry 6 (256), 2023 | 4 | 2023 |
| G-PLIP: Knowledge graph neural network for structure-free protein-ligand bioactivity prediction SJ Crouzet, AM Lieberherr, K Atz, T Nilsson, L Sach-Peltason, AT Müller, ... Computational and Structural Biology Journal, 2024 | 2 | 2024 |
| Graph transformer neural network for chemical reactivity prediction DF Nippa, K Atz, AT Müller, J Wolfard, C Isert, M Binder, O Scheidegger, ... | 2 | 2023 |
| De novo design of antimicrobial peptides: from sequence templates to artificial intelligence AT Müller PhD Thesis, 2018 | 2 | 2018 |
| Combining Graph Attention and Recurrent Neural Networks in a Variational Autoencoder for Molecular Representation Learning and Drug Design AT Müller, K Atz, M Reutlinger, N Zorn ICML 2024, ML4LMS Workshop, 2024 | 1* | 2024 |
| Geometric deep learning-guided Suzuki reaction conditions assessment for applications in medicinal chemistry K Atz, D Nippa, A Mueller, V Jost, A Anelli, M Reutlinger, C Kramer, ... RSC Medicinal Chemistry, 2024 | 1 | 2024 |
| Simple User-Friendly Reaction Format DF Nippa, AT Müller, K Atz, DB Konrad, U Grether, RE Martin, ... | 1 | 2023 |
| Small-Molecule-Directed Endogenous Regeneration of Visual Function in a Mammalian Retinal Degeneration Model D Mokady, J Charish, P Barretto-Burns, KN Grisé, BLK Coles, S Raab, ... International Journal of Molecular Sciences 25 (3), 1521, 2024 | | 2024 |
Gisbert SchneiderETH ZurichVerified email at ethz.ch
