| ColabFold-Making protein folding accessible to all M Mirdita, K Schuetze, Y Moriwaki, L Heo, S Ovchinnikov, M Steinegger Nature Methods 19, 679-682, 2022 | 3831 | 2022 |
| GalaxyRefine: Protein structure refinement driven by side-chain repacking L Heo, H Park, C Seok Nucleic acids research 41 (W1), W384-W388, 2013 | 877 | 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 | 699 | 2012 |
| GalaxyPepDock: a protein–peptide docking tool based on interaction similarity and energy optimization H Lee, L Heo, MS Lee, C Seok Nucleic acids research 43 (W1), W431-W435, 2015 | 244 | 2015 |
| Prediction of protein structure and interaction by GALAXY protein modeling programs WH Shin, GR Lee, L Heo, H Lee, C Seok Biodesign 2, 1-11, 2014 | 188 | 2014 |
| Advances in GPCR modeling evaluated by the GPCR Dock 2013 assessment: meeting new challenges I Kufareva, V Katritch, RC Stevens, R Abagyan Structure 22 (8), 1120-1139, 2014 | 181 | 2014 |
| Prediction of homoprotein and heteroprotein complexes by protein docking and template‐based modeling: a CASP‐CAPRI experiment MF Lensink, S Velankar, A Kryshtafovych, SY Huang, ... Proteins: Structure, Function, and Bioinformatics 84, 323-348, 2016 | 164 | 2016 |
| GalaxyHomomer: a web server for protein homo-oligomer structure prediction from a monomer sequence or structure M Baek, T Park, L Heo, C Park, C Seok Nucleic acids research 45 (W1), W320-W324, 2017 | 119 | 2017 |
| GalaxyRefineComplex: Refinement of protein-protein complex model structures driven by interface repacking L Heo, H Lee, C Seok Scientific reports 6 (1), 32153, 2016 | 108 | 2016 |
| GalaxySite: ligand-binding-site prediction by using molecular docking L Heo, WH Shin, MS Lee, C Seok Nucleic acids research 42 (W1), W210-W214, 2014 | 105 | 2014 |
| Effective protein model structure refinement by loop modeling and overall relaxation GR Lee, L Heo, C Seok Proteins: Structure, Function, and Bioinformatics 84, 293-301, 2016 | 103 | 2016 |
| The challenge of modeling protein assemblies: the CASP12‐CAPRI experiment MF Lensink, S Velankar, M Baek, L Heo, C Seok, SJ Wodak Proteins: Structure, Function, and Bioinformatics 86, 257-273, 2018 | 92 | 2018 |
| 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 | 91 | 2014 |
| GalaxyRefine2: simultaneous refinement of inaccurate local regions and overall protein structure GR Lee, J Won, L Heo, C Seok Nucleic acids research 47 (W1), W451-W455, 2019 | 89 | 2019 |
| Multi-state Modeling of G-protein Coupled Receptors at Experimental Accuracy L Heo, M Feig Proteins: Structure, Function, and Bioinformatics 90, 1873–1885, 2022 | 84 | 2022 |
| Experimental accuracy in protein structure refinement via molecular dynamics simulations L Heo, M Feig Proceedings of the National Academy of Sciences 115 (52), 13276-13281, 2018 | 80 | 2018 |
| Modeling of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) proteins by machine learning and physics-based refinement L Heo, M Feig BioRxiv, 2020 | 68 | 2020 |
| High‐accuracy protein structures by combining machine‐learning with physics‐based refinement L Heo, M Feig Proteins: Structure, Function, and Bioinformatics 88 (5), 637-642, 2020 | 56 | 2020 |
| LigDockCSA: protein–ligand docking using conformational space annealing WH Shin, L Heo, J Lee, J Ko, C Seok, J Lee Journal of computational chemistry 32 (15), 3226-3232, 2011 | 52 | 2011 |
| Direct Generation of Protein Conformational Ensembles via Machine Learning G Janson, G Valdes-Garcia, L Heo, M Feig Nature Communications 14, 774, 2023 | 48 | 2023 |
Chaok SeokSeoul National UniversityVerified email at snu.ac.kr
