Baek, Minkyung

Accurate prediction of protein structures and interactions using a 3-track network

Baek, M., DiMaio, F., Anishchenko, I., Dauparas, J., Ovchinnikov, S., Lee, G. R., Wang, J., Cong, Q., Kinch, L. N., Schaeffer, R. D., et al. (2021) · Science

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 5,549

Broadly applicable and accurate protein design by integrating structure prediction networks and diffusion generative models

Watson, J. L., Juergens, D., Bennett, N. R., Trippe, B. L., Yim, J., Eisenach, H. E., Ahern, W., Borst, A. J., Ragotte, R. J., Milles, L. F., et al. (2022) · Nature

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 2,369

De novo design of protein structure and function with RFdiffusion

Watson, J. L., Juergens, D., Bennett, N. R., Trippe, B. L., Yim, J., Eisenach, H. E., Ahern, W., Borst, A. J., Ragotte, R. J., Milles, L. F., et al. (2023) · Nature

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 2,325

Generalized biomolecular modeling and design with RoseTTAFold All-Atom

Krishna, R., Wang, J., Ahern, W., Sturmfels, P., Venkatesh, P., Kalvet, I., Lee, G. R., Morey-Burrows, F. S., Anishchenko, I., Humphreys, I. R., et al. (2024) · Science

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 978

Computed structures of core eukaryotic protein complexes

Humphreys, I. R., Pei, J., Baek, M., Krishnakumar, A., Anishchenko, I., Ovchinnikov, S., Zhang, J., Ness, T. J., Banjade, S., Bagde, S. R., et al. (2021) · Science

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 542

Structures of core eukaryotic protein complexes

Humphreys, I. R., Pei, J., Baek, M., Krishnakumar, A., Anishchenko, I., Ovchinnikov, S., Zhang, J., Ness, T. J., Banjade, S., Bagde, S., et al. (2021) · Science

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 541

Deep learning methods for designing proteins scaffolding functional sites

Wang, J., Lisanza, S., Juergens, D., Tischer, D., Anishchenko, I., Baek, M., Watson, J. L., Chun, J. H., Milles, L. F., Dauparas, J., et al. (2021) · Science

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 487

Scaffolding protein functional sites using deep learning

Wang, J., Lisanza, S., Juergens, D., Tischer, D., Watson, J. L., Castro, K. M., Ragotte, R., Saragovi, A., Milles, L. F., Baek, M., et al. (2022) · Science

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 487

Improving de novo protein binder design with deep learning

Bennett, N. R., Coventry, B., Goreshnik, I., Huang, B., Allen, A., Vafeados, D., Peng, Y. P., Dauparas, J., Baek, M., Stewart, L., et al. (2023) · Nature Communications

Protein Structure and Dynamicsvaccines and immunoinformatics approaches

Cited by 402

Accurate prediction of protein–nucleic acid complexes using RoseTTAFoldNA

Baek, M., McHugh, R., Anishchenko, I., Jiang, H., Baker, D., & DiMaio, F. (2024) · Nature Methods

Protein Structure and DynamicsRNA and protein synthesis mechanisms

Cited by 372

Improved protein structure refinement guided by deep learning based accuracy estimation

Hiranuma, N., Park, H., Baek, M., Anishchenko, I., Dauparas, J., & Baker, D. (2021) · Nature Communications

Protein Structure and DynamicsEnzyme Structure and Function

Cited by 243

Hallucinating symmetric protein assemblies

Wicky, B. I. M., Milles, L. F., Courbet, A., Ragotte, R. J., Dauparas, J., Kinfu, E., Tipps, S., Kibler, R. D., Baek, M., DiMaio, F., et al. (2022) · Science

Protein Structure and DynamicsEnzyme Structure and Function

Cited by 240

Hallucinating protein assemblies

Wicky, B. I. M., Milles, L. F., Courbet, A., Ragotte, R. J., Dauparas, J., Kinfu, E., Tipps, S., Kibler, R. D., Baek, M., DiMaio, F., et al. (2022) · Science

Protein Structure and DynamicsEnzyme Structure and Function

Cited by 240

Peptide-binding specificity prediction using fine-tuned protein structure prediction networks

Motmaen, A., Dauparas, J., Baek, M., Abedi, M. H., Baker, D., & Bradley, P. (2023) · Proceedings of the National Academy of Sciences

vaccines and immunoinformatics approachesProtein Structure and Dynamics

Cited by 124

Blind prediction of homo- and hetero-protein complexes: the CASP13-CAPRI experiment

Lensink, M. F., Brysbaert, G., Nadzirin, N., Velankar, S., Chaleil, R. A. G., Gerguri, T., Bates, P. A., Laine, E., Carbone, A., Grudinin, S., et al. (2019) · Proteins Structure Function and Bioinformatics

Protein Structure and DynamicsEnzyme Structure and Function

Cited by 122

Generalized Biomolecular Modeling and Design with RoseTTAFold All-Atom

Krishna, R., Wang, J., Ahern, W., Sturmfels, P., Venkatesh, P., Kalvet, I., Lee, G. R., Morey-Burrows, F. S., Anishchenko, I., Humphreys, I. R., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory)

Protein Structure and DynamicsComputational Drug Discovery Methods

Cited by 106

Predicting protein-protein interactions in the human proteome

Zhang, J., Humphreys, I. R., Pei, J., Kim, J., Choi, C., Yuan, R., Durham, J., Liu, S., Choi, H.-J., Baek, M., et al. (2025) · Science

Bioinformatics and Genomic NetworksProtein Structure and Dynamics

Cited by 87

Democratizing Protein Language Models with Parameter-Efficient Fine-Tuning

Sledzieski, S., Kshirsagar, M., Baek, M., Berger, B., Dodhia, R., & Ferres, J. L. (2023) · Proceedings of the National Academy of Sciences

Machine Learning in BioinformaticsProtein Structure and Dynamics

Cited by 86

Democratizing protein language models with parameter-efficient fine-tuning

Sledzieski, S., Kshirsagar, M., Baek, M., Dodhia, R., Lavista Ferres, J., & Berger, B. (2024) · Proceedings of the National Academy of Sciences

Machine Learning in BioinformaticsProtein Structure and Dynamics

Cited by 86

The ΦPA3 Phage Nucleus is Enclosed by a Self-Assembling, 2D Crystalline Lattice

Nieweglowska, E., Brilot, A., Méndez-Moran, M., Baek, M., Li, J., Kokontis, C., Cheng, Y., Baker, D., Bondy-Denomy, J., & Agard, D. (2022) · Nature Communications

Bacteriophages and microbial interactionsAdvanced Electron Microscopy Techniques and Applications

Cited by 45

Protein–protein interactions in the Mla lipid transport system probed by computational structure prediction and deep mutational scanning

MacRae, M. R., Puvanendran, D., Haase, M. A. B., Coudray, N., Kolich, L., Lam, C., Baek, M., Bhabha, G., & Ekiert, D. C. (2023) · Journal of Biological Chemistry

Bacterial Genetics and BiotechnologyLipid Membrane Structure and Behavior

Cited by 23

Rapid and accurate prediction of protein homo-oligomer symmetry using Seq2Symm

Kshirsagar, M., Meller, A., Humphreys, I. R., Sledzieski, S., Xu, Y., Dodhia, R., Horvitz, E., Berger, B., Bowman, G. R., Ferres, J. L., et al. (2025) · Nature Communications

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 23

Rapid and accurate prediction of protein homo-oligomer symmetry with Seq2Symm

Kshirsagar, M., Meller, A., Humphreys, I., Sledzieski, S., Xu, Y., Dodhia, R., Horvitz, E., Berger, B., Bowman, G., Ferres, J. L., et al. (2024) · Nature Communications

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 22

Protein oligomer modeling guided by predicted interchain contacts in CASP14

Baek, M., Anishchenko, I., Park, H., Humphreys, I. R., & Baker, D. (2021) · Proteins: Structure, Function, and Bioinformatics

Protein Structure and DynamicsEnzyme Structure and Function

Cited by 18