Found 287 results
Heinzinger M, Littmann M, Sillitoe I, Bordin N, Orengo C, Rost B. Contrastive learning on protein embeddings enlightens midnight zone. NAR Genom Bioinform. 2022 ;4(2):lqac043.
Foley G, Mora A, Ross CM, Bottoms S, Sützl L, Lamprecht ML, Zaugg J, Essebier A, Balderson B, Newell R, et al. Engineering indel and substitution variants of diverse and ancient enzymes using Graphical Representation of Ancestral Sequence Predictions (GRASP). PLoS Comput Biol. 2022 ;18(10):e1010633.
Olenyi T, Marquet C, Heinzinger M, Kröger B, Nikolova T, Bernhofer M, Sändig P, Schütze K, Littmann M, Mirdita M, et al. LambdaPP: Fast and accessible protein-specific phenotype predictions. Protein Sci. 2022 :e4524.
Schütze K, Heinzinger M, Steinegger M, Rost B. Nearest neighbor search on embeddings rapidly identifies distant protein relations. Front Bioinform. 2022 ;2:1033775.
Bordin N, Dallago C, Heinzinger M, Kim S, Littmann M, Rauer C, Steinegger M, Rost B, Orengo C. Novel machine learning approaches revolutionize protein knowledge. Trends Biochem Sci. 2022 .
Weissenow K, Heinzinger M, Rost B. Protein language-model embeddings for fast, accurate, and alignment-free protein structure prediction. Structure. 2022 .
Lautenbacher L, Samaras P, Muller J, Grafberger A, Shraideh M, Rank J, Fuchs ST, Schmidt TK, The M, Dallago C, et al. ProteomicsDB: toward a FAIR open-source resource for life-science research. Nucleic Acids Res. 2022 ;50(D1):D1541-D1552.
Ilzhöfer D, Heinzinger M, Rost B. SETH predicts nuances of residue disorder from protein embeddings. Front Bioinform. 2022 ;2:1019597.
Bernhofer M, Rost B. TMbed: transmembrane proteins predicted through language model embeddings. BMC Bioinformatics. 2022 ;23(1):326.
Littmann M, Bordin N, Heinzinger M, Schütze K, Dallago C, Orengo C, Rost B. Clustering FunFams using sequence embeddings improves EC purity. Bioinformatics. 2021 .
Littmann M, Heinzinger M, Dallago C, Olenyi T, Rost B. Embeddings from deep learning transfer GO annotations beyond homology. Sci Rep. 2021 ;11(1):1160.
Marquet C, Heinzinger M, Olenyi T, Dallago C, Erckert K, Bernhofer M, Nechaev D, Rost B. Embeddings from protein language models predict conservation and variant effects. Hum Genet. 2021 .
Dallago C, Schütze K, Heinzinger M, Olenyi T, Littmann M, Lu AX, Yang KK, Min S, Yoon S, Morton JT, et al. Learned Embeddings from Deep Learning to Visualize and Predict Protein Sets. Curr Protoc. 2021 ;1(5):e113.
Bernhofer M, Dallago C, Karl T, Satagopam V, Heinzinger M, Littmann M, Olenyi T, Qiu J, Schütze K, Yachdav G, et al. PredictProtein - Predicting Protein Structure and Function for 29 Years. Nucleic Acids Res. 2021 ;49(W1):W535-W540.
Littmann M, Heinzinger M, Dallago C, Weissenow K, Rost B. Protein embeddings and deep learning predict binding residues for various ligand classes. Sci Rep. 2021 ;11(1):23916.
Heinzinger M, Dallago C, Rost B. Protein matchmaking through representation learning. Cell Syst. 2021 ;12(10):948-950.
Elnaggar A, Heinzinger M, Dallago C, Rehawi G, Yu W, Jones L, Gibbs T, Feher T, Angerer C, Steinegger M, et al. ProtTrans: Towards Cracking the Language of Lifes Code Through Self-Supervised Deep Learning and High Performance Computing. IEEE Trans Pattern Anal Mach Intell. 2021 ;PP.
O'Donoghue SI, Schafferhans A, Sikta N, Stolte C, Kaur S, Ho BK, Anderson S, Procter JB, Dallago C, Bordin N, et al. SARS-CoV-2 structural coverage map reveals viral protein assembly, mimicry, and hijacking mechanisms. Mol Syst Biol. 2021 ;17(9):e10079.
Marot-Lassauzaie V, Goldberg T, Armenteros JJuan Almag, Nielsen H, Rost B. Spectrum of Protein Location in Proteomes Captures Evolutionary Relationship Between Species. J Mol Evol. 2021 .
Peeken JC, Goldberg T, Pyka T, Bernhofer M, Wiestler B, Kessel KA, Tafti PD, Nüsslin F, Braun AE, Zimmer C, et al. Combining multimodal imaging and treatment features improves machine learning-based prognostic assessment in patients with glioblastoma multiforme. Cancer Med. 2018 .
Marot-Lassauzaie V, Bernhofer M, Rost B. Correcting mistakes in predicting distributions. Bioinformatics. 2018 .
Schafferhans A, O'Donoghue SI, Heinzinger M, Rost B. Dark Proteins Important for Cellular Function. Proteomics. 2018 ;18(21-22):e1800227.
Schelling M, Hopf TA, Rost B. Evolutionary couplings and sequence variation effect predict protein binding sites. Proteins. 2018 .
Mahlich Y, Steinegger M, Rost B, Bromberg Y. HFSP: high speed homology-driven function annotation of proteins. Bioinformatics. 2018 ;34(13):i304-i312.
Cejuela JMiguel, Vinchurkar S, Goldberg T, Shankar MSollepura, Baghudana A, Bojchevski A, Uhlig C, Ofner A, Raharja-Liu P, Jensen LJuhl, et al. LocText: relation extraction of protein localizations to assist database curation. BMC Bioinformatics. 2018 ;19(1):15.
Bernhofer M, Goldberg T, Wolf S, Ahmed M, Zaugg J, Boden M, Rost B. NLSdb-major update for database of nuclear localization signals and nuclear export signals. Nucleic Acids Res. 2018 ;46(D1):D503-D508.
Tran L, Hamp T, Rost B. ProfPPIdb: Pairs of physical protein-protein interactions predicted for entire proteomes. PLoS One. 2018 ;13(7):e0199988.
Peeken JC, Bernhofer M, Wiestler B, Goldberg T, Cremers D, Rost B, Wilkens JJ, Combs SE, Nüsslin F. Radiomics in radiooncology - Challenging the medical physicist. Phys Med. 2018 ;48:27-36.
Sanghai ZAssur, Liu Q, Clarke OB, Belcher-Dufrisne M, Wiriyasermkul P, M Giese H, Leal-Pinto E, Kloss B, Tabuso S, Love J, et al. Structure-based analysis of CysZ-mediated cellular uptake of sulfate. Elife. 2018 ;7.
Cevost J, Vaillant C, Meyer S, Rost B. ThreaDNA: predicting DNA mechanics' contribution to sequence selectivity of proteins along whole genomes. Bioinformatics. 2018 ;34(4):609-616.
Peeken JC, Goldberg T, Knie C, Komboz B, Bernhofer M, Pasa F, Kessel KA, Tafti PD, Rost B, Nüsslin F, et al. Treatment-related features improve machine learning prediction of prognosis in soft tissue sarcoma patients. Strahlenther Onkol. 2018 ;194(9):824-834.