Heinzinger, Michael

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

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

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

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

From sequence to function through structure: deep learning for protein design

Ferruz, N., Heinzinger, M., Akdel, M., Goncearenco, A., Naef, L., & Dallago, C. (2022) · Computational and Structural Biotechnology Journal

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 124

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

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

Protein Structure Informed Bacteriophage Genome Annotation with Phold

Bouras, G., Grigson, S. R., Mirdita, M., Heinzinger, M., Papudeshi, B., Mallawaarachchi, V., Green, R., Kim, R. S., Mihalia, V., Psaltis, A. J., et al. (2025) · Nucleic Acids Research

Bacteriophages and microbial interactionsGenomics and Phylogenetic Studies

Cited by 71

Protein structure-informed bacteriophage genome annotation with Phold

Bouras, G., Grigson, S. R., Mirdita, M., Heinzinger, M., Papudeshi, B., Mallawaarachchi, V., Green, R., Kim, R. S., Mihalia, V., Psaltis, A. J., et al. (2026) · Nucleic Acids Research

Bacteriophages and microbial interactionsGenomics and Phylogenetic Studies

Cited by 71

CATHe: detection of remote homologues for CATH superfamilies using embeddings from protein language models

Nallapareddy, V., Bordin, N., Sillitoe, I., Heinzinger, M., Littmann, M., Waman, V. P., Sen, N., Rost, B., & Orengo, C. (2023) · Bioinformatics

Machine Learning in BioinformaticsProtein Structure and Dynamics

Cited by 47

Democratizing protein language model training, sharing and collaboration

Su, J., Li, Z., Tao, T., Han, C., He, Y., Dai, F., Yuan, Q., Gao, Y., Si, T., Zhang, X., et al. (2026) · Nature Biotechnology

Machine Learning in BioinformaticsProtein Structure and Dynamics

Cited by 35

Protein Embeddings Predict Binding Residues in Disordered Regions

Jahn, L. R., Marquet, C., Heinzinger, M., & Rost, B. (2024) · Scientific Reports

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 28

LambdaPP: Fast and accessible protein-specific phenotype predictions

Olenyi, T., Marquet, C., Heinzinger, M., Kröger, B., Nikolova, T., Bernhofer, M., Sändig, P., Schütze, K., Littmann, M., Mirdita, M., et al. (2022) · Protein Science

Machine Learning in BioinformaticsProtein Structure and Dynamics

Cited by 18