| ProtTrans: Towards Cracking the Language of Lifes Code Through Self-Supervised Deep Learning and High Performance Computing A Elnaggar, M Heinzinger, C Dallago, G Rihawi, Y Wang, L Jones, ... IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021 | 252 | 2021 |
| Modeling aspects of the language of life through transfer-learning protein sequences M Heinzinger, A Elnaggar, Y Wang, C Dallago, D Nechaev, F Matthes, ... BMC bioinformatics 20 (1), 1-17, 2019 | 184 | 2019 |
| Embeddings from deep learning transfer GO annotations beyond homology M Littmann, M Heinzinger, C Dallago, T Olenyi, B Rost Scientific reports 11 (1), 1-14, 2021 | 37 | 2021 |
| 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 | 36 | 2021 |
| ProNA2020 predicts protein–DNA, protein–RNA, and protein–protein binding proteins and residues from sequence J Qiu, M Bernhofer, M Heinzinger, S Kemper, T Norambuena, F Melo, ... Journal of molecular biology 432 (7), 2428-2443, 2020 | 24 | 2020 |
| 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 | 20 | 2021 |
| Light attention predicts protein location from the language of life H Stärk, C Dallago, M Heinzinger, B Rost Bioinformatics Advances 1 (1), vbab035, 2021 | 12 | 2021 |
| Protein language-model embeddings for fast, accurate, and alignment-free protein structure prediction K Weißenow, M Heinzinger, B Rost Structure, 2022 | 11 | 2022 |
| 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 | 10 | 2021 |
| End-to-end multitask learning, from protein language to protein features without alignments A Elnaggar, M Heinzinger, C Dallago, B Rost bioRxiv, 864405, 2020 | 9* | 2020 |
| Embeddings from protein language models predict conservation and variant effects C Marquet, M Heinzinger, T Olenyi, C Dallago, K Erckert, M Bernhofer, ... Human genetics, 1-19, 2021 | 6 | 2021 |
| Protein embeddings and deep learning predict binding residues for various ligand classes M Littmann, M Heinzinger, C Dallago, K Weissenow, B Rost Scientific Reports 11 (1), 1-15, 2021 | 6 | 2021 |
| Family-specific analysis of variant pathogenicity prediction tools J Zaucha, M Heinzinger, S Tarnovskaya, B Rost, D Frishman NAR genomics and bioinformatics 2 (2), lqaa014, 2020 | 6 | 2020 |
| Dark proteins important for cellular function A Schafferhans, SI O'Donoghue, M Heinzinger, B Rost Proteomics 18 (21-22), 1800227, 2018 | 6 | 2018 |
| CATHe: Detection of remote homologues for CATH superfamilies using embeddings from protein language models V Nallapareddy, N Bordin, I Sillitoe, M Heinzinger, M Littmann, V Waman, ... bioRxiv, 2022 | 5 | 2022 |
| Mutations in transmembrane proteins: diseases, evolutionary insights, prediction and comparison with globular proteins J Zaucha, M Heinzinger, A Kulandaisamy, E Kataka, ÓL Salvádor, ... Briefings in Bioinformatics 22 (3), bbaa132, 2021 | 5 | 2021 |
| Contrastive learning on protein embeddings enlightens midnight zone M Heinzinger, M Littmann, I Sillitoe, N Bordin, C Orengo, B Rost NAR genomics and bioinformatics 4 (2), lqac043, 2022 | 1* | 2022 |
| Bee core venom genes predominantly originated before aculeate stingers evolved I Koludarov, M Velasque, T Timm, G Lochnit, M Heinzinger, A Vilcinskas, ... bioRxiv, 2022 | 1 | 2022 |
| The identification of microplastics based on vibrational spectroscopy data–A critical review of data analysis routines J Weisser, T Pohl, M Heinzinger, NP Ivleva, T Hofmann, K Glas TrAC Trends in Analytical Chemistry, 116535, 2022 | | 2022 |
| AlphaFold2 reveals commonalities and novelties in protein structure space for 21 model organisms N Bordin, I Sillitoe, MV Nallapareddy, C Rauer, SD Lam, VP Waman, ... bioRxiv, 2022 | | 2022 |
Burkhard RostProfessor of Computer Science & Computational Biology & Bioinformatics, TUM, MunichVerified email at tum.de
