| In silico proof of principle of machine learning-based antibody design at unconstrained scale R Akbar, PA Robert, CR Weber, M Widrich, R Frank, M Pavlović, ... Mabs 14 (1), 2031482, 2022 | 84 | 2022 |
| Progress and challenges for the machine learning-based design of fit-for-purpose monoclonal antibodies R Akbar, H Bashour, P Rawat, PA Robert, E Smorodina, TS Cotet, ... Mabs 14 (1), 2008790, 2022 | 61 | 2022 |
| The immuneML ecosystem for machine learning analysis of adaptive immune receptor repertoires M Pavlović, L Scheffer, K Motwani, C Kanduri, R Kompova, N Vazov, ... Nature Machine Intelligence 3 (11), 936-944, 2021 | 59 | 2021 |
| One billion synthetic 3D-antibody-antigen complexes enable unconstrained machine-learning formalized investigation of antibody specificity prediction PA Robert, R Akbar, R Frank, M Pavlović, M Widrich, I Snapkov, ... Nature Computational Science, 845–865, 2022 | 24 | 2022 |
