Park, Hahnbeom
Korea Institute of Science and Technology · Sungkyunkwan University
11 papers on CoChatORCID 0000-0002-7129-1912
Most cited papers
- Verified
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
- Verified
The Rosetta All-Atom Energy Function for Macromolecular Modeling and Design
Alford, R. F., Leaver-Fay, A., Jeliazkov, J. R., O’Meara, M. J., DiMaio, F. P., Park, H., Shapovalov, M. V., Renfrew, P. D., Mulligan, V. K., Kappel, K., et al. (2017) · Journal of Chemical Theory and Computation
Protein Structure and DynamicsRNA and protein synthesis mechanisms
Cited by 1,532
- Verified
Improved protein structure prediction using predicted interresidue orientations
Yang, J., Anishchenko, I., Park, H., Peng, Z., Ovchinnikov, S., & Baker, D. (2020) · Proceedings of the National Academy of Sciences
Protein Structure and DynamicsEnzyme Structure and Function
Cited by 1,421
- Verified
Macromolecular modeling and design in Rosetta: recent methods and frameworks
Leman, J. K., Weitzner, B. D., Lewis, S. M., Adolf-Bryfogle, J., Alam, N., Alford, R. F., Aprahamian, M., Baker, D., Barlow, K. A., Barth, P., et al. (2020) · Nature Methods
Protein Structure and DynamicsComputational Drug Discovery Methods
Cited by 888
- Verified
Protein structure determination using metagenome sequence data
Ovchinnikov, S., Park, H., Varghese, N., Huang, P.-S., Pavlopoulos, G. A., Kim, D. E., Kamisetty, H., Kyrpides, N. C., & Baker, D. (2017) · Science
Protein Structure and DynamicsEnzyme Structure and Function
Cited by 520
- Verified
De novo design of a fluorescence-activating β-barrel
Dou, J., Vorobieva, A. A., Sheffler, W., Doyle, L. A., Park, H., Bick, M. J., Mao, B., Foight, G. W., Lee, M. Y., Gagnon, L. A., et al. (2018) · Nature
Protein Structure and DynamicsBiochemical and Structural Characterization
Cited by 351
- Verified
An artificial intelligence accelerated virtual screening platform for drug discovery
Zhou, G., Rusnac, D.-V., Park, H., Canzani, D., Nguyen, H. M., Stewart, L., Bush, M. F., Nguyen, P. T., Wulff, H., Yarov-Yarovoy, V., et al. (2024) · Nature Communications
Computational Drug Discovery Methodsvaccines and immunoinformatics approaches
Cited by 260
- Verified
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
- Verified
Large-scale determination of previously unsolved protein structures using evolutionary information
Ovchinnikov, S., Kinch, L., Park, H., Liao, Y., Pei, J., Kim, D. E., Kamisetty, H., Grishin, N. V., & Baker, D. (2015) · eLife
Protein Structure and DynamicsEnzyme Structure and Function
Cited by 222
- Verified
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
- Verified
Deep learning molecular interaction motifs from receptor structures alone
Kim, S., Oh, S., Woo, H., Sim, J., Seok, C., & Park, H. (2025) · Journal of Cheminformatics
Computational Drug Discovery MethodsProtein Structure and Dynamics
Cited by 3
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