Hahnbeom Park
Cited by
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Accurate prediction of protein structures and interactions using a three-track neural network
M Baek, F DiMaio, I Anishchenko, J Dauparas, S Ovchinnikov, GR Lee, ...
Science 373 (6557), 871-876, 2021
Improved protein structure prediction using predicted interresidue orientations
J Yang, I Anishchenko, H Park, Z Peng, S Ovchinnikov, D Baker
Proceedings of the National Academy of Sciences 117 (3), 1496-1503, 2020
The Rosetta all-atom energy function for macromolecular modeling and design
RF Alford, A Leaver-Fay, JR Jeliazkov, MJ O’Meara, FP DiMaio, H Park, ...
Journal of chemical theory and computation 13 (6), 3031-3048, 2017
GalaxyRefine: Protein structure refinement driven by side-chain repacking
L Heo, H Park, C Seok
Nucleic acids research 41 (W1), W384-W388, 2013
GalaxyWEB server for protein structure prediction and refinement
J Ko, H Park, L Heo, C Seok
Nucleic acids research 40 (W1), W294-W297, 2012
Macromolecular modeling and design in Rosetta: recent methods and frameworks
JK Leman, BD Weitzner, SM Lewis, J Adolf-Bryfogle, N Alam, RF Alford, ...
Nature methods 17 (7), 665-680, 2020
Protein structure determination using metagenome sequence data
S Ovchinnikov, H Park, N Varghese, PS Huang, GA Pavlopoulos, DE Kim, ...
Science 355 (6322), 294-298, 2017
Simultaneous optimization of biomolecular energy functions on features from small molecules and macromolecules
H Park, P Bradley, P Greisen Jr, Y Liu, VK Mulligan, DE Kim, D Baker, ...
Journal of chemical theory and computation 12 (12), 6201-6212, 2016
De novo design of a fluorescence-activating β-barrel
J Dou, AA Vorobieva, W Sheffler, LA Doyle, H Park, MJ Bick, B Mao, ...
Nature 561 (7724), 485-491, 2018
Large-scale determination of previously unsolved protein structures using evolutionary information
S Ovchinnikov, L Kinch, H Park, Y Liao, J Pei, DE Kim, H Kamisetty, ...
elife 4, e09248, 2015
Improved protein structure refinement guided by deep learning based accuracy estimation
N Hiranuma, H Park, M Baek, I Anishchenko, J Dauparas, D Baker
Nature communications 12 (1), 1340, 2021
Conditioning by adaptive sampling for robust design
D Brookes, H Park, J Listgarten
International conference on machine learning, 773-782, 2019
Community-wide assessment of protein-interface modeling suggests improvements to design methodology
SJ Fleishman, TA Whitehead, EM Strauch, JE Corn, S Qin, HX Zhou, ...
Journal of molecular biology 414 (2), 289-302, 2011
Protein loop modeling by using fragment assembly and analytical loop closure
J Lee, D Lee, H Park, EA Coutsias, C Seok
Proteins: Structure, Function, and Bioinformatics 78 (16), 3428-3436, 2010
Protein structure prediction using Rosetta in CASP12
S Ovchinnikov, H Park, DE Kim, F DiMaio, D Baker
Proteins: Structure, Function, and Bioinformatics 86, 113-121, 2018
Community‐wide evaluation of methods for predicting the effect of mutations on protein–protein interactions
R Moretti, SJ Fleishman, R Agius, M Torchala, PA Bates, PL Kastritis, ...
Proteins: Structure, Function, and Bioinformatics 81 (11), 1980-1987, 2013
GalaxyTBM: template-based modeling by building a reliable core and refining unreliable local regions
J Ko, H Park, C Seok
BMC bioinformatics 13, 1-8, 2012
The FALC-Loop web server for protein loop modeling
J Ko, D Lee, H Park, EA Coutsias, J Lee, C Seok
Nucleic acids research 39 (suppl_2), W210-W214, 2011
Protein loop modeling using a new hybrid energy function and its application to modeling in inaccurate structural environments
H Park, GR Lee, L Heo, C Seok
PloS one 9 (11), e113811, 2014
Refinement of unreliable local regions in template‐based protein models
H Park, C Seok
Proteins: Structure, Function, and Bioinformatics 80 (8), 1974-1986, 2012
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