Lim Heo

14.9k total citations · 4 hit papers
38 papers, 8.3k citations indexed

About

Lim Heo is a scholar working on Molecular Biology, Materials Chemistry and Spectroscopy. According to data from OpenAlex, Lim Heo has authored 38 papers receiving a total of 8.3k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Molecular Biology, 24 papers in Materials Chemistry and 7 papers in Spectroscopy. Recurrent topics in Lim Heo's work include Protein Structure and Dynamics (27 papers), Enzyme Structure and Function (24 papers) and Mass Spectrometry Techniques and Applications (7 papers). Lim Heo is often cited by papers focused on Protein Structure and Dynamics (27 papers), Enzyme Structure and Function (24 papers) and Mass Spectrometry Techniques and Applications (7 papers). Lim Heo collaborates with scholars based in United States, South Korea and Japan. Lim Heo's co-authors include Milot Mirdita, Konstantin Schütze, Yoshitaka Moriwaki, Sergey Ovchinnikov, Martin Steinegger, Chaok Seok, Hahnbeom Park, Michael Feig, Jin Hwan Ko and Hasup Lee and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Nature Communications.

In The Last Decade

Lim Heo

38 papers receiving 8.2k citations

Hit Papers

ColabFold: making prote... 2012 2026 2016 2021 2022 2013 2012 2022 1000 2.0k 3.0k 4.0k 5.0k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Lim Heo United States 23 6.1k 899 773 755 712 38 8.3k
Ben Webb United States 12 6.9k 1.1× 1.1k 1.2× 689 0.9× 746 1.0× 503 0.7× 13 9.5k
M. S. Madhusudhan India 28 6.6k 1.1× 1.1k 1.3× 774 1.0× 687 0.9× 380 0.5× 67 9.2k
David Eramian United States 7 6.0k 1.0× 818 0.9× 674 0.9× 696 0.9× 385 0.5× 8 8.3k
Rosalba Lepore Italy 15 5.7k 0.9× 514 0.6× 777 1.0× 954 1.3× 521 0.7× 27 9.3k
Narayanan Eswar United States 25 8.4k 1.4× 1.3k 1.4× 802 1.0× 775 1.0× 545 0.8× 52 11.2k
Rafal Gumienny Switzerland 10 6.2k 1.0× 586 0.7× 745 1.0× 996 1.3× 546 0.8× 10 9.9k
Gerardo Tauriello Switzerland 15 6.4k 1.1× 600 0.7× 778 1.0× 1.1k 1.4× 600 0.8× 22 10.5k
Sergey Ovchinnikov United States 31 7.9k 1.3× 1.5k 1.7× 519 0.7× 462 0.6× 751 1.1× 71 10.6k
Tjaart de Beer United Kingdom 14 6.5k 1.1× 621 0.7× 799 1.0× 1.1k 1.4× 582 0.8× 25 10.7k
Min‐Yi Shen United States 14 7.6k 1.2× 1.3k 1.5× 782 1.0× 827 1.1× 443 0.6× 20 10.4k

Countries citing papers authored by Lim Heo

Since Specialization
Citations

This map shows the geographic impact of Lim Heo's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Lim Heo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lim Heo more than expected).

Fields of papers citing papers by Lim Heo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lim Heo. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Lim Heo. The network helps show where Lim Heo may publish in the future.

Co-authorship network of co-authors of Lim Heo

This figure shows the co-authorship network connecting the top 25 collaborators of Lim Heo. A scholar is included among the top collaborators of Lim Heo based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Lim Heo. Lim Heo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Janson, Giacomo, et al.. (2023). Direct generation of protein conformational ensembles via machine learning. Nature Communications. 14(1). 774–774. 96 indexed citations
2.
Heo, Lim & Michael Feig. (2023). One bead per residue can describe all-atom protein structures. Structure. 32(1). 97–111.e6. 24 indexed citations
4.
Heo, Lim, Yuji Sugita, & Michael Feig. (2022). Protein assembly and crowding simulations. Current Opinion in Structural Biology. 73. 102340–102340. 26 indexed citations
5.
Heo, Lim, et al.. (2021). Improved Sampling Strategies for Protein Model Refinement Based on Molecular Dynamics Simulation. Journal of Chemical Theory and Computation. 17(3). 1931–1943. 16 indexed citations
6.
Heo, Lim, Giacomo Janson, & Michael Feig. (2021). Physics‐based protein structure refinement in the era of artificial intelligence. Proteins Structure Function and Bioinformatics. 89(12). 1870–1887. 16 indexed citations
7.
Baek, Minkyung, Taeyong Park, Lim Heo, & Chaok Seok. (2020). Modeling Protein Homo-Oligomer Structures with GalaxyHomomer Web Server. Methods in molecular biology. 2165. 127–137. 4 indexed citations
8.
Heo, Lim & Michael Feig. (2018). Experimental accuracy in protein structure refinement via molecular dynamics simulations. Proceedings of the National Academy of Sciences. 115(52). 13276–13281. 60 indexed citations
9.
Feig, Michael & Lim Heo. (2018). Protein Structure Refinement via Molecular Dynamics Simulations. Biophysical Journal. 114(3). 575a–575a. 3 indexed citations
10.
Lensink, Marc F., Sameer Velankar, Minkyung Baek, et al.. (2017). The challenge of modeling protein assemblies: the CASP12‐CAPRI experiment. Proteins Structure Function and Bioinformatics. 86(S1). 257–273. 80 indexed citations
11.
Baek, Minkyung, Taeyong Park, Lim Heo, Chiwook Park, & Chaok Seok. (2017). GalaxyHomomer: a web server for protein homo-oligomer structure prediction from a monomer sequence or structure. Nucleic Acids Research. 45(W1). W320–W324. 93 indexed citations
12.
Heo, Lim & Michael Feig. (2017). PREFMD: a web server for protein structure refinement via molecular dynamics simulations. Bioinformatics. 34(6). 1063–1065. 31 indexed citations
13.
Heo, Lim, Hasup Lee, Minkyung Baek, & Chaok Seok. (2016). Binding Site Prediction of Proteins with Organic Compounds or Peptides Using GALAXY Web Servers. Methods in molecular biology. 1414. 33–45. 6 indexed citations
14.
Singh, Atul K., et al.. (2015). Factors affecting redox potential and differential sensitivity ofSoxRto redox‐active compounds. Molecular Microbiology. 97(5). 808–821. 17 indexed citations
15.
Lee, Gyu Rie, Lim Heo, & Chaok Seok. (2015). Effective protein model structure refinement by loop modeling and overall relaxation. Proteins Structure Function and Bioinformatics. 84(S1). 293–301. 96 indexed citations
16.
Lee, Hasup, Lim Heo, Myeong Sup Lee, & Chaok Seok. (2015). GalaxyPepDock: a protein–peptide docking tool based on interaction similarity and energy optimization. Nucleic Acids Research. 43(W1). W431–W435. 229 indexed citations
17.
Park, Hahnbeom, Gyu Rie Lee, Lim Heo, & Chaok Seok. (2014). Protein Loop Modeling Using a New Hybrid Energy Function and Its Application to Modeling in Inaccurate Structural Environments. PLoS ONE. 9(11). e113811–e113811. 70 indexed citations
18.
Heo, Lim, Hahnbeom Park, & Chaok Seok. (2013). GalaxyRefine: protein structure refinement driven by side-chain repacking. Nucleic Acids Research. 41(W1). W384–W388. 948 indexed citations breakdown →
19.
Heo, Lim, et al.. (2013). Alternative zinc‐binding sites explain the redox sensitivity of zinc‐containing anti‐sigma factors. Proteins Structure Function and Bioinformatics. 81(9). 1644–1652. 6 indexed citations
20.
Shin, Woong‐Hee, Lim Heo, Juyong Lee, et al.. (2011). LigDockCSA: Protein–ligand docking using conformational space annealing. Journal of Computational Chemistry. 32(15). 3226–3232. 35 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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