InSuk Joung

960 total citations
22 papers, 662 citations indexed

About

InSuk Joung is a scholar working on Molecular Biology, Materials Chemistry and Computational Theory and Mathematics. According to data from OpenAlex, InSuk Joung has authored 22 papers receiving a total of 662 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Molecular Biology, 13 papers in Materials Chemistry and 5 papers in Computational Theory and Mathematics. Recurrent topics in InSuk Joung's work include Protein Structure and Dynamics (15 papers), Enzyme Structure and Function (10 papers) and Computational Drug Discovery Methods (5 papers). InSuk Joung is often cited by papers focused on Protein Structure and Dynamics (15 papers), Enzyme Structure and Function (10 papers) and Computational Drug Discovery Methods (5 papers). InSuk Joung collaborates with scholars based in South Korea, United States and Japan. InSuk Joung's co-authors include Thomas Steinbrecher, David A. Case, Jooyoung Lee, Sunhwan Jo, Nathan R. Kern, Hui Sun Lee, Sang‐Jun Park, Yifei Qi, Wonpil Im and Jumin Lee and has published in prestigious journals such as Nature Communications, The Journal of Chemical Physics and Bioinformatics.

In The Last Decade

InSuk Joung

20 papers receiving 653 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
InSuk Joung South Korea 11 470 186 82 81 79 22 662
Shawn Witham United States 10 559 1.2× 120 0.6× 86 1.0× 61 0.8× 40 0.5× 12 738
Dawei Zhang China 12 352 0.7× 125 0.7× 59 0.7× 57 0.7× 68 0.9× 33 495
Z. Nevin Gerek United States 14 508 1.1× 178 1.0× 62 0.8× 109 1.3× 47 0.6× 17 707
Aaron T. Frank United States 17 654 1.4× 127 0.7× 31 0.4× 82 1.0× 111 1.4× 36 838
Shubhra Ghosh Dastidar India 16 559 1.2× 121 0.7× 56 0.7× 97 1.2× 46 0.6× 55 754
Joseph D. Yesselman United States 16 777 1.7× 100 0.5× 76 0.9× 55 0.7× 66 0.8× 26 930
Aleksandra E. Badaczewska-Dawid Poland 11 849 1.8× 388 2.1× 87 1.1× 141 1.7× 93 1.2× 21 1.1k
Samuela Pasquali France 16 814 1.7× 165 0.9× 54 0.7× 58 0.7× 52 0.7× 40 937
Arianna Fornili United Kingdom 18 506 1.1× 152 0.8× 154 1.9× 54 0.7× 76 1.0× 42 803

Countries citing papers authored by InSuk Joung

Since Specialization
Citations

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

Fields of papers citing papers by InSuk Joung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of InSuk Joung

This figure shows the co-authorship network connecting the top 25 collaborators of InSuk Joung. A scholar is included among the top collaborators of InSuk Joung 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 InSuk Joung. InSuk Joung 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.
2.
Ji, Hyunjun, et al.. (2024). Quantum-Informed Molecular Representation Learning Enhancing ADMET Property Prediction. Journal of Chemical Information and Modeling. 64(13). 5028–5040. 6 indexed citations
3.
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
4.
Yoo, Jiho, et al.. (2023). Industrializing AI/ML during the end-to-end drug discovery process. Current Opinion in Structural Biology. 79. 102528–102528. 11 indexed citations
5.
Joung, InSuk, Jong Yun Kim, Keehyoung Joo, & Jooyoung Lee. (2019). Non-sequential protein structure alignment by conformational space annealing and local refinement. PLoS ONE. 14(1). e0210177–e0210177. 2 indexed citations
6.
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
7.
8.
Park, Sang‐Jun, Jumin Lee, Yifei Qi, et al.. (2019). CHARMM-GUIGlycan Modelerfor modeling and simulation of carbohydrates and glycoconjugates. Glycobiology. 29(4). 320–331. 236 indexed citations
9.
Joo, Keehyoung, et al.. (2018). Data‐assisted protein structure modeling by global optimization in CASP12. Proteins Structure Function and Bioinformatics. 86(S1). 240–246. 4 indexed citations
10.
Hong, Seung Hwan, InSuk Joung, Balachandran Manavalan, et al.. (2017). Protein structure modeling and refinement by global optimization in CASP12. Proteins Structure Function and Bioinformatics. 86(S1). 122–135. 15 indexed citations
11.
Lee, Juyong, et al.. (2017). Finding Dominant Reaction Pathways via Global Optimization of Action. Biophysical Journal. 112(3). 290a–290a. 1 indexed citations
12.
Lee, Juyong, In‐Ho Lee, InSuk Joung, Jooyoung Lee, & Bernard R. Brooks. (2017). Finding multiple reaction pathways via global optimization of action. Nature Communications. 8(1). 15443–15443. 28 indexed citations
13.
Cheng, Qianyi, InSuk Joung, & Jooyoung Lee. (2017). A Simple and Efficient Protein Structure Refinement Method. Journal of Chemical Theory and Computation. 13(10). 5146–5162. 9 indexed citations
14.
Lee, Jooyoung, Keehyoung Joo, InSuk Joung, et al.. (2016). Protein Structure Determination by Conformational Space Annealing using NMR Geometric Restraints. Biophysical Journal. 110(3). 188a–188a.
15.
Joo, Keehyoung, InSuk Joung, Jinhyuk Lee, et al.. (2015). Protein structure determination by conformational space annealing using NMR geometric restraints. Proteins Structure Function and Bioinformatics. 83(12). 2251–2262. 12 indexed citations
16.
Joo, Keehyoung, InSuk Joung, Sun‐Young Lee, et al.. (2015). Template based protein structure modeling by global optimization in CASP11. Proteins Structure Function and Bioinformatics. 84(S1). 221–232. 28 indexed citations
17.
Lee, Juyong, Kiho Lee, InSuk Joung, et al.. (2015). Sigma-RF: prediction of the variability of spatial restraints in template-based modeling by random forest. BMC Bioinformatics. 16(1). 16 indexed citations
18.
Joo, Keehyoung, InSuk Joung, Qianyi Cheng, Sung Jong Lee, & Jooyoung Lee. (2015). Contact‐assisted protein structure modeling by global optimization in CASP11. Proteins Structure Function and Bioinformatics. 84(S1). 189–199. 14 indexed citations
19.
Manavalan, Balachandran, Kunihiro Kuwajima, InSuk Joung, & Jooyoung Lee. (2015). Structure-based protein folding type classification and folding rate prediction. 12. 1759–1761. 5 indexed citations
20.
Steinbrecher, Thomas, InSuk Joung, & David A. Case. (2011). Soft‐core potentials in thermodynamic integration: Comparing one‐ and two‐step transformations. Journal of Computational Chemistry. 32(15). 3253–3263. 182 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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