Juyong Lee

2.8k total citations
100 papers, 1.7k citations indexed

About

Juyong Lee is a scholar working on Molecular Biology, Materials Chemistry and Computational Theory and Mathematics. According to data from OpenAlex, Juyong Lee has authored 100 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Molecular Biology, 26 papers in Materials Chemistry and 17 papers in Computational Theory and Mathematics. Recurrent topics in Juyong Lee's work include Protein Structure and Dynamics (34 papers), Computational Drug Discovery Methods (17 papers) and Enzyme Structure and Function (14 papers). Juyong Lee is often cited by papers focused on Protein Structure and Dynamics (34 papers), Computational Drug Discovery Methods (17 papers) and Enzyme Structure and Function (14 papers). Juyong Lee collaborates with scholars based in South Korea, United States and Puerto Rico. Juyong Lee's co-authors include Chaok Seok, Bernard R. Brooks, Jooyoung Lee, Young Jin Youn, Khagendra Dahal, Junsu Ko, Jharendra Rijal, Ana Damjanović, Benjamin T. Miller and Woong‐Hee Shin and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Juyong Lee

92 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Juyong Lee South Korea	26	872	386	378	226	217	100	1.7k
Diane Joseph‐McCarthy United States	32	1.7k 2.0×	547 1.4×	408 1.1×	509 2.3×	354 1.6×	78	2.8k
H. Nakamura Japan	26	1.5k 1.7×	208 0.5×	386 1.0×	243 1.1×	505 2.3×	97	3.5k
Alexander Hillisch Germany	28	1.4k 1.6×	705 1.8×	255 0.7×	163 0.7×	157 0.7×	57	2.8k
Axel Meißner Germany	28	1.1k 1.3×	57 0.1×	205 0.5×	438 1.9×	83 0.4×	114	2.3k
Brian Kelley United States	25	1.9k 2.1×	1.5k 3.8×	877 2.3×	43 0.2×	561 2.6×	61	3.6k
Hans Matter Germany	33	1.9k 2.2×	1.4k 3.6×	531 1.4×	76 0.3×	98 0.5×	102	3.5k
Christine Lee United States	21	1.9k 2.2×	110 0.3×	92 0.2×	40 0.2×	201 0.9×	51	3.3k
Chris Ho United States	21	448 0.5×	164 0.4×	240 0.6×	129 0.6×	550 2.5×	32	1.6k
Nadhipuram V. Bhagavan United States	21	846 1.0×	29 0.1×	92 0.2×	160 0.7×	125 0.6×	40	1.4k
Matthew Wright United States	25	472 0.5×	174 0.5×	44 0.1×	205 0.9×	84 0.4×	85	1.8k

Countries citing papers authored by Juyong Lee

Since Specialization

Citations

This map shows the geographic impact of Juyong Lee'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 Juyong Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Juyong Lee more than expected).

Fields of papers citing papers by Juyong Lee

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Juyong Lee. 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 Juyong Lee. The network helps show where Juyong Lee may publish in the future.

Co-authorship network of co-authors of Juyong Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Juyong Lee. A scholar is included among the top collaborators of Juyong Lee 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 Juyong Lee. Juyong Lee is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Lee, Juyong, et al.. (2025). Refining EI-MS library search results through atomic-level insights. Communications Chemistry. 8(1). 332–332.

Lee, Juyong, et al.. (2025). Recent advances in AI-driven protein-ligand interaction predictions. Current Opinion in Structural Biology. 92. 103020–103020. 11 indexed citations

Lee, Juyong, et al.. (2025). Automated and Efficient Sampling of Chemical Reaction Space. Advanced Science. 12(9). e2409009–e2409009. 2 indexed citations

Jin, S., et al.. (2025). A survey on large language models in biology and chemistry. Experimental & Molecular Medicine.

Kim, Jong Seung, Cheulhee Jung, Nam‐Jung Kim, et al.. (2024). Discovery of thiophen-2-ylmethylene bis-dimedone derivatives as novel WRN inhibitors for treating cancers with microsatellite instability. Bioorganic & Medicinal Chemistry. 100. 117588–117588. 6 indexed citations

Lee, Juyong, et al.. (2024). Improving docking and virtual screening performance using AlphaFold2 multi-state modeling for kinases. Scientific Reports. 14(1). 25167–25167. 1 indexed citations

Lee, Jihyeon, Hyunbin Kim, Stephanie Kim, et al.. (2024). Discovery of highly active kynureninases for cancer immunotherapy through protein language model. Nucleic Acids Research. 53(1). 4 indexed citations

Byun, Jinyoung, et al.. (2023). Characterization of the role of Kunitz‐type protease inhibitor domain in dimerization of amyloid precursor protein. Journal of Computational Chemistry. 44(15). 1437–1445. 4 indexed citations

Lee, Juyong, et al.. (2023). Reconstruction of lossless molecular representations from fingerprints. Journal of Cheminformatics. 15(1). 26–26. 12 indexed citations

10.

Yi, Jee Hyun, Kyoung Ja Kwon, Seungheon Lee, et al.. (2023). Aβ dissociation by pectolinarin may counteract against Aβ-induced synaptic dysfunction and memory impairment. Biochemical Pharmacology. 216. 115792–115792. 2 indexed citations

11.

Lee, Juyong, et al.. (2023). Efficient discovery of multiple minimum action pathways using Gaussian process. Journal of Physics Communications. 7(2). 25004–25004. 2 indexed citations

12.

Hong, Yiyu, et al.. (2022). S-Pred: protein structural property prediction using MSA transformer. Scientific Reports. 12(1). 13891–13891. 5 indexed citations

13.

Ko, Junsu, et al.. (2022). Retrosynthetic reaction pathway prediction through neural machine translation of atomic environments. Nature Communications. 13(1). 1186–1186. 57 indexed citations

14.

Cheng, Qianyi, et al.. (2019). Exploring the Folding Mechanism of Small Proteins GB1 and LB1. Journal of Chemical Theory and Computation. 15(6). 3432–3449. 3 indexed citations

15.

Dahal, Khagendra, Jharendra Rijal, Sharan Prakash Sharma, et al.. (2017). Comparison of manual compression and vascular hemostasis devices after coronary angiography or percutaneous coronary intervention through femoral artery access: A meta-analysis of randomized controlled trials. Cardiovascular revascularization medicine. 19(2). 151–162. 8 indexed citations

16.

Dahal, Khagendra, Sharan Prakash Sharma, Erik Fung, et al.. (2015). Meta-analysis of Randomized Controlled Trials of Genotype-Guided vs Standard Dosing of Warfarin. CHEST Journal. 148(3). 701–710. 27 indexed citations

17.

Malik, Adeel, et al.. (2014). Community-Based Network Study of Protein-Carbohydrate Interactions in Plant Lectins Using Glycan Array Data. PLoS ONE. 9(4). e95480–e95480. 15 indexed citations

18.

Joo, Keehyoung, Juyong Lee, Sun‐Young Lee, et al.. (2013). Protein structure modeling for CASP10 by multiple layers of global optimization. Proteins Structure Function and Bioinformatics. 82(S2). 188–195. 33 indexed citations

19.

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

20.

Lee, Juyong, Masaki Sasai, Chaok Seok, & Jooyoung Lee. (2010). de Novo Protein Structure Prediction using Fragment Based Potential and Conformational Space Annealing. Biophysical Journal. 98(3). 461a–461a. 1 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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