Rost, Burkhard

ProtTrans: Toward Understanding the Language of Life Through Self-Supervised Learning

Elnaggar, A., Heinzinger, M., Dallago, C., Rehawi, G., Wang, Y., Jones, L., Gibbs, T., Feher, T., Angerer, C., Steinegger, M., et al. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Machine Learning in BioinformaticsProtein Structure and Dynamics

Cited by 2,329

Twilight zone of protein sequence alignments

Rost, B. (1999) · Protein Engineering, Design and Selection

Protein Structure and DynamicsEnzyme Structure and Function

Cited by 1,833

A large-scale evaluation of computational protein function prediction

Radivojac, P., Clark, W. T., Oron, T. R., Schnoes, A. M., Wittkop, T., Sokolov, A., Graim, K., Funk, C., Verspoor, K., Ben-Hur, A., et al. (2013) · Nature Methods

Bioinformatics and Genomic NetworksMachine Learning in Bioinformatics

Cited by 1,028

A draft network of ligand–receptor-mediated multicellular signalling in human

Ramilowski, J. A., Goldberg, T., Harshbarger, J., Kloppmann, E., Lizio, M., Satagopam, V. P., Itoh, M., Kawaji, H., Carninci, P., Rost, B., et al. (2015) · Nature Communications

Bioinformatics and Genomic NetworksGene Regulatory Network Analysis

Cited by 887

Modeling the language of life – Deep Learning Protein Sequences

Heinzinger, M., Elnaggar, A., Wang, Y., Dallago, C., Nechaev, D., Matthes, F., & Rost, B. (2019) · BMC Bioinformatics

Machine Learning in BioinformaticsProtein Structure and Dynamics

Cited by 606

Modeling aspects of the language of life through transfer-learning protein sequences

Heinzinger, M., Elnaggar, A., Wang, Y., Dallago, C., Nechaev, D., Matthes, F., & Rost, B. (2019) · BMC Bioinformatics

Machine Learning in BioinformaticsProtein Structure and Dynamics

Cited by 606

The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

Zhou, N., Jiang, Y., Bergquist, T. R., Lee, A. J., Kacsoh, B. Z., Crocker, A. W., Lewis, K. A., Georghiou, G., Nguyen, H. N., Hamid, M. N., et al. (2019) · Genome Biology

Bioinformatics and Genomic NetworksGenomics and Phylogenetic Studies

Cited by 452

Bilingual Language Model for Protein Sequence and Structure

Heinzinger, M., Weissenow, K., Sanchez, J. G., Henkel, A., Mirdita, M., Steinegger, M., & Rost, B. (2023) · NAR Genomics and Bioinformatics

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 312

Bilingual language model for protein sequence and structure

Heinzinger, M., Weissenow, K., Sanchez, J. G., Henkel, A., Mirdita, M., Steinegger, M., & Rost, B. (2024) · NAR Genomics and Bioinformatics

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 311

Fine-tuning protein language models boosts predictions across diverse tasks

Schmirler, R., Heinzinger, M., & Rost, B. (2024) · Nature Communications

Machine Learning in BioinformaticsProtein Structure and Dynamics

Cited by 229

Fine-tuning protein language models boosts predictions across diverse tasks

Schmirler, R., Heinzinger, M., & Rost, B. (2023) · Nature Communications

Machine Learning in BioinformaticsProtein Structure and Dynamics

Cited by 229

Embeddings from protein language models predict conservation and variant effects

Marquet, C., Heinzinger, M., Olenyi, T., Dallago, C., Bernhofer, M., Erckert, K., Nechaev, D., & Rost, B. (2021) · Human Genetics

Machine Learning in BioinformaticsProtein Structure and Dynamics

Cited by 174

Embeddings from protein language models predict conservation and variant effects

Marquet, C., Heinzinger, M., Olenyi, T., Dallago, C., Bernhofer, M., Erckert, K., Nechaev, D., & Rost, B. (2021) · Human Genetics

Machine Learning in BioinformaticsProtein Structure and Dynamics

Cited by 174

Embeddings from protein language models predict conservation and variant effects

Marquet, C., Heinzinger, M., Olenyi, T., Dallago, C., Bernhofer, M., Erckert, K., & Rost, B. (2021) · Human Genetics

Machine Learning in BioinformaticsProtein Structure and Dynamics

Cited by 174

Structure and activity of tryptophan-rich TSPO proteins

Guo, Y., Kalathur, R. C., Liu, Q., Kloss, B., Bruni, R., Ginter, C., Kloppmann, E., Rost, B., & Hendrickson, W. A. (2015) · Science

Enzyme Structure and FunctionPorphyrin Metabolism and Disorders

Cited by 171

Protein language model embeddings for fast, accurate, alignment-free protein structure prediction

Weissenow, K., Heinzinger, M., & Rost, B. (2021) · Structure

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 139

Light attention predicts protein location from the language of life

Stärk, H., Dallago, C., Heinzinger, M., & Rost, B. (2021) · Bioinformatics Advances

Machine Learning in BioinformaticsProtein Structure and Dynamics

Cited by 130

Protein embeddings and deep learning predict binding residues for various ligand classes

Littmann, M., Heinzinger, M., Dallago, C., Weissenow, K., & Rost, B. (2021) · Scientific Reports

Machine Learning in BioinformaticsProtein Structure and Dynamics

Cited by 120

Contrastive learning on protein embeddings enlightens midnight zone

Heinzinger, M., Littmann, M., Sillitoe, I., Bordin, N., Orengo, C., & Rost, B. (2021) · NAR Genomics and Bioinformatics

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 105

AlphaFold2 reveals commonalities and novelties in protein structure space for 21 model organisms

Bordin, N., Sillitoe, I., Nallapareddy, V., Rauer, C., Lam, S. D., Waman, V. P., Sen, N., Heinzinger, M., Littmann, M., Kim, S., et al. (2022) · Communications Biology

Protein Structure and DynamicsEnzyme Structure and Function

Cited by 103

AlphaFold2 reveals commonalities and novelties in protein structure space for 21 model organisms

Bordin, N., Sillitoe, I., Nallapareddy, V., Rauer, C., Lam, S. D., Waman, V. P., Sen, N., Heinzinger, M., Littmann, M., Kim, S., et al. (2023) · Communications Biology

Protein Structure and DynamicsEnzyme Structure and Function

Cited by 103

Radiomics in radiooncology – challenging the medical physicist

Peeken, J. C., Bernhofer, M., Wiestler, B., Goldberg, T., Cremers, D., Rost, B., Wilkens, J. J., Combs, S. E., & Nüsslin, F. (2018) · Physica Medica

Radiomics and Machine Learning in Medical ImagingArtificial Intelligence in Healthcare and Education

Cited by 98

Novel machine learning approaches revolutionize protein knowledge

Bordin, N., Dallago, C., Heinzinger, M., Kim, S., Littmann, M., Rauer, C., Steinegger, M., Rost, B., & Orengo, C. (2023) · Trends in Biochemical Sciences

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 72

Validity of machine learning in biology and medicine increased through collaborations across fields of expertise

Littmann, M., Selig, K., Cohen-Lavi, L., Frank, Y., Hönigschmid, P., Kataka, E., Mösch, A., Qian, K., Ron, A., Schmid, S., et al. (2020) · Nature Machine Intelligence

Interdisciplinary Research and Collaborationscientometrics and bibliometrics research

Cited by 70