| ColabFold: making protein folding accessible to all M Mirdita, K Schütze, Y Moriwaki, L Heo, S Ovchinnikov, M Steinegger Nature methods 19 (6), 679-682, 2022 | 3921 | 2022 |
| PredictProtein-predicting protein structure and function for 29 years M Bernhofer, C Dallago, T Karl, V Satagopam, M Heinzinger, M Littmann, ... Nucleic acids research 49 (W1), W535-W540, 2021 | 168 | 2021 |
| Learned embeddings from deep learning to visualize and predict protein sets C Dallago, K Schütze, M Heinzinger, T Olenyi, M Littmann, AX Lu, ... Current Protocols 1 (5), e113, 2021 | 68 | 2021 |
| Clustering FunFams using sequence embeddings improves EC purity M Littmann, N Bordin, M Heinzinger, K Schütze, C Dallago, C Orengo, ... Bioinformatics 37 (20), 3449-3455, 2021 | 24 | 2021 |
| Nearest neighbor search on embeddings rapidly identifies distant protein relations K Schütze, M Heinzinger, M Steinegger, B Rost Frontiers in Bioinformatics 2, 1033775, 2022 | 22 | 2022 |
| LambdaPP: Fast and accessible protein‐specific phenotype predictions T Olenyi, C Marquet, M Heinzinger, B Kröger, T Nikolova, M Bernhofer, ... Protein Science 32 (1), e4524, 2023 | 7 | 2023 |
| Labelizer: systematic selection of protein residues for covalent fluorophore labeling C Gebhardt, P Bawidamann, K Schuetze, GG Moya Munoz, AK Spring, ... bioRxiv, 2023.06. 12.544586, 2023 | 1 | 2023 |
