Jejoong Yoo

4.0k total citations
58 papers, 2.8k citations indexed

About

Jejoong Yoo is a scholar working on Molecular Biology, Biomedical Engineering and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Jejoong Yoo has authored 58 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Molecular Biology, 21 papers in Biomedical Engineering and 13 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Jejoong Yoo's work include Nanopore and Nanochannel Transport Studies (16 papers), DNA and Nucleic Acid Chemistry (16 papers) and Lipid Membrane Structure and Behavior (14 papers). Jejoong Yoo is often cited by papers focused on Nanopore and Nanochannel Transport Studies (16 papers), DNA and Nucleic Acid Chemistry (16 papers) and Lipid Membrane Structure and Behavior (14 papers). Jejoong Yoo collaborates with scholars based in United States, South Korea and United Kingdom. Jejoong Yoo's co-authors include Aleksei Aksimentiev, Qiang Cui, Christopher Maffeo, Swati Bhattacharya, Ulrich F. Keyser, Taekjip Ha, Chen-Yu Li, Alexander Ohmann, Kerstin Göpfrich and David B. Wells and has published in prestigious journals such as Chemical Reviews, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.

In The Last Decade

Jejoong Yoo

58 papers receiving 2.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jejoong Yoo United States 29 2.2k 892 307 269 213 58 2.8k
Bryant S. Fujimoto United States 29 1.6k 0.7× 626 0.7× 306 1.0× 400 1.5× 225 1.1× 76 2.4k
Hanbin Mao United States 38 3.1k 1.4× 1.3k 1.4× 463 1.5× 186 0.7× 255 1.2× 111 4.2k
Nam Ki Lee South Korea 26 1.8k 0.8× 268 0.3× 333 1.1× 287 1.1× 129 0.6× 59 3.0k
Liming Ying United Kingdom 37 2.6k 1.2× 1.2k 1.4× 544 1.8× 739 2.7× 128 0.6× 102 4.6k
Joachim D. Müller United States 32 2.2k 1.0× 549 0.6× 557 1.8× 439 1.6× 62 0.3× 54 3.5k
Valentin Gordeliy Russia 32 2.3k 1.1× 369 0.4× 262 0.9× 554 2.1× 111 0.5× 166 3.6k
Jagannath Mondal India 27 1.3k 0.6× 305 0.3× 275 0.9× 518 1.9× 151 0.7× 131 2.2k
Alexander Kotlyar Israel 34 2.7k 1.2× 483 0.5× 328 1.1× 540 2.0× 194 0.9× 117 3.8k
Nancy C. Stellwagen United States 32 1.6k 0.7× 1.8k 2.0× 286 0.9× 159 0.6× 187 0.9× 97 3.2k
Noriko Inada Japan 27 1.3k 0.6× 468 0.5× 243 0.8× 813 3.0× 65 0.3× 54 3.3k

Countries citing papers authored by Jejoong Yoo

Since Specialization
Citations

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

Fields of papers citing papers by Jejoong Yoo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jejoong Yoo

This figure shows the co-authorship network connecting the top 25 collaborators of Jejoong Yoo. A scholar is included among the top collaborators of Jejoong Yoo 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 Jejoong Yoo. Jejoong Yoo 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.
Jang, Seo Young, et al.. (2025). Structural basis for malate-driven, pore lipid-regulated activation of the Arabidopsis vacuolar anion channel ALMT9. Nature Communications. 16(1). 1817–1817. 2 indexed citations
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Jeong, Ki‐Baek, Jinsik Kim, Minsoo Kim, et al.. (2023). Single-molecule fingerprinting of protein-drug interaction using a funneled biological nanopore. Nature Communications. 14(1). 1461–1461. 43 indexed citations
5.
Jeong, Hyeongseop, et al.. (2023). Cryo-EM structures of human Cx36/GJD2 neuronal gap junction channel. Nature Communications. 14(1). 1347–1347. 17 indexed citations
6.
Kim, Minsoo, InSuk Joung, Sung Jong Lee, et al.. (2023). DeepFold: enhancing protein structure prediction through optimized loss functions, improved template features, and re-optimized energy function. Bioinformatics. 39(12). 10 indexed citations
7.
Kim, Minsoo, et al.. (2022). Aggregation or phase separation can be induced in highly charged proteins by small charged biomolecules. Soft Matter. 18(17). 3313–3317. 2 indexed citations
8.
Jeong, Hyeongseop, et al.. (2020). Cryo-EM structure of human Cx31.3/GJC3 connexin hemichannel. Science Advances. 6(35). eaba4996–eaba4996. 52 indexed citations
9.
Kim, Kimoon, et al.. (2020). Improved Parameterization of Protein–DNA Interactions for Molecular Dynamics Simulations of PCNA Diffusion on DNA. Journal of Chemical Theory and Computation. 16(7). 4006–4013. 22 indexed citations
10.
Park, Kyeng Min, Kangkyun Baek, Young Ho Ko, et al.. (2018). Mono‐allyloxylated Cucurbit[7]uril Acts as an Unconventional Amphiphile To Form Light‐Responsive Vesicles. Angewandte Chemie. 130(12). 3186–3190. 9 indexed citations
11.
Yoo, Jejoong, Chenyu Li, & Aleksei Aksimentiev. (2016). Membrane-Spanning DNA Ion Channels: Conductance Mechanism, Electro-Osmotic Transport and Mechanical Gating. Biophysical Journal. 110(3). 119a–119a. 1 indexed citations
12.
Göpfrich, Kerstin, Chen-Yu Li, Maria Ricci, et al.. (2016). Large-Conductance Transmembrane Porin Made from DNA Origami. ACS Nano. 10(9). 8207–8214. 156 indexed citations
13.
Yoo, Jejoong & Aleksei Aksimentiev. (2015). Improved Parameterization of Amine–Carboxylate and Amine–Phosphate Interactions for Molecular Dynamics Simulations Using the CHARMM and AMBER Force Fields. Journal of Chemical Theory and Computation. 12(1). 430–443. 132 indexed citations
14.
Yoo, Jejoong & Aleksei Aksimentiev. (2014). In Situ Structure and Dynamics of DNA Origami Determined Through Molecular Dynamics Simulations. Biophysical Journal. 106(2). 695a–695a. 3 indexed citations
15.
Yoo, Jejoong & Aleksei Aksimentiev. (2013). In situ structure and dynamics of DNA origami determined through molecular dynamics simulations. Proceedings of the National Academy of Sciences. 110(50). 20099–20104. 123 indexed citations
16.
Yoo, Jejoong & Qiang Cui. (2013). Three-Dimensional Stress Field around a Membrane Protein: Atomistic and Coarse-Grained Simulation Analysis of Gramicidin A. Biophysical Journal. 104(1). 117–127. 23 indexed citations
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Chen, Xi, Qiang Cui, Yuye Tang, Jejoong Yoo, & Arun Yethiraj. (2008). Gating Mechanisms of Mechanosensitive Channels of Large Conductance, I: A Continuum Mechanics-Based Hierarchical Framework. Biophysical Journal. 95(2). 563–580. 33 indexed citations
19.
Tang, Yuye, Jejoong Yoo, Arun Yethiraj, Qiang Cui, & Xi Chen. (2008). Gating Mechanisms of Mechanosensitive Channels of Large Conductance, II: Systematic Study of Conformational Transitions. Biophysical Journal. 95(2). 581–596. 21 indexed citations
20.
Tang, Yuye, Guoxin Cao, Xi Chen, et al.. (2006). A Finite Element Framework for Studying the Mechanical Response of Macromolecules: Application to the Gating of the Mechanosensitive Channel MscL. Biophysical Journal. 91(4). 1248–1263. 56 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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