Kee‐Choo Chung

741 total citations
20 papers, 666 citations indexed

About

Kee‐Choo Chung is a scholar working on Spectroscopy, Radiology, Nuclear Medicine and Imaging and Nuclear and High Energy Physics. According to data from OpenAlex, Kee‐Choo Chung has authored 20 papers receiving a total of 666 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Spectroscopy, 6 papers in Radiology, Nuclear Medicine and Imaging and 6 papers in Nuclear and High Energy Physics. Recurrent topics in Kee‐Choo Chung's work include NMR spectroscopy and applications (6 papers), Advanced NMR Techniques and Applications (6 papers) and Computational Drug Discovery Methods (4 papers). Kee‐Choo Chung is often cited by papers focused on NMR spectroscopy and applications (6 papers), Advanced NMR Techniques and Applications (6 papers) and Computational Drug Discovery Methods (4 papers). Kee‐Choo Chung collaborates with scholars based in South Korea, United States and Vietnam. Kee‐Choo Chung's co-authors include Sangdoo Ahn, Suk‐Kyu Chang, Ki Cheol Song, Jun Soo Kim, Hwangseo Park, G. W. Crabtree, Zhao Zhang, Peter J. Hesketh, L. E. DeLong and B. Ilic and has published in prestigious journals such as Physical review. B, Condensed matter, The Journal of Physical Chemistry C and International Journal of Molecular Sciences.

In The Last Decade

Kee‐Choo Chung

18 papers receiving 655 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kee‐Choo Chung South Korea 10 254 179 161 126 124 20 666
K. V. Ramanathan India 19 547 2.2× 469 2.6× 63 0.4× 185 1.5× 84 0.7× 111 1.2k
Han‐Qing Wu China 18 156 0.6× 320 1.8× 44 0.3× 267 2.1× 52 0.4× 34 855
Sándor Holly Hungary 15 151 0.6× 144 0.8× 121 0.8× 235 1.9× 98 0.8× 45 812
A. N. Kiselev Russia 12 90 0.4× 231 1.3× 25 0.2× 61 0.5× 44 0.4× 47 432
Udo Benedikt Germany 9 130 0.5× 171 1.0× 19 0.1× 162 1.3× 43 0.3× 13 751
Stephen Parus United States 10 125 0.5× 78 0.4× 87 0.5× 88 0.7× 105 0.8× 14 440
Hiroaki Utsumi Japan 14 207 0.8× 293 1.6× 40 0.2× 113 0.9× 105 0.8× 35 644
David Semin United States 15 295 1.2× 140 0.8× 14 0.1× 57 0.5× 252 2.0× 42 821
Claire Loison France 15 120 0.5× 79 0.4× 97 0.6× 181 1.4× 350 2.8× 33 646

Countries citing papers authored by Kee‐Choo Chung

Since Specialization
Citations

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

Fields of papers citing papers by Kee‐Choo Chung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kee‐Choo Chung. 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 Kee‐Choo Chung. The network helps show where Kee‐Choo Chung may publish in the future.

Co-authorship network of co-authors of Kee‐Choo Chung

This figure shows the co-authorship network connecting the top 25 collaborators of Kee‐Choo Chung. A scholar is included among the top collaborators of Kee‐Choo Chung 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 Kee‐Choo Chung. Kee‐Choo Chung 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.
Chung, Kee‐Choo, et al.. (2023). Derivation of Highly Predictive 3D-QSAR Models for hERG Channel Blockers Based on the Quantum Artificial Neural Network Algorithm. Pharmaceuticals. 16(11). 1509–1509. 4 indexed citations
2.
Kim, Taeho, et al.. (2021). Quantum Artificial Neural Network Approach to Derive a Highly Predictive 3D-QSAR Model for Blood–Brain Barrier Passage. International Journal of Molecular Sciences. 22(20). 10995–10995. 15 indexed citations
3.
Choi, Hwanho, Hongsuk Kang, Kee‐Choo Chung, & Hwangseo Park. (2019). Development and application of a comprehensive machine learning program for predicting molecular biochemical and pharmacological properties. Physical Chemistry Chemical Physics. 21(9). 5189–5199. 11 indexed citations
4.
Choi, Hwanho, Kee‐Sun Sohn, Myoungho Pyo, Kee‐Choo Chung, & Hwangseo Park. (2019). Predicting the Electrochemical Properties of Lithium-Ion Battery Electrode Materials with the Quantum Neural Network Algorithm. The Journal of Physical Chemistry C. 123(8). 4682–4690. 12 indexed citations
5.
Prabakar, S. J. Richard, Amol Bhairuba Ikhe, Woon Bae Park, et al.. (2019). Graphite as a Long‐Life Ca2+‐Intercalation Anode and its Implementation for Rocking‐Chair Type Calcium‐Ion Batteries. Advanced Science. 6(24). 1902129–1902129. 69 indexed citations
6.
Chung, Kee‐Choo, et al.. (2018). A Numerical Study on the Dynamics of Distant Dipolar Field in Solution NMR: Understanding Spatial Aspect of Magnetizations. Bulletin of the Korean Chemical Society. 39(10). 1223–1226.
7.
Chung, Kee‐Choo & Hwangseo Park. (2016). Extended solvent-contact model approach to blind SAMPL5 prediction challenge for the distribution coefficients of drug-like molecules. Journal of Computer-Aided Molecular Design. 30(11). 1019–1033. 6 indexed citations
8.
Chung, Kee‐Choo & Hwangseo Park. (2015). Accuracy enhancement in the estimation of molecular hydration free energies by implementing the intramolecular hydrogen bond effects. Journal of Cheminformatics. 7(1). 57–57. 10 indexed citations
9.
Chung, Kee‐Choo, et al.. (2013). Analytical and Numerical Calculations of Diffusion Effects on the Intermolecular Multiple Quantum Coherences in Solution NMR. Bulletin of the Korean Chemical Society. 34(12). 3895–3898. 4 indexed citations
10.
11.
Cho, Jee‐Hyun, et al.. (2011). Experimental Analyses on Contrast Behaviors of iDQC and iTQC MR Images at 4.7 T. Bulletin of the Korean Chemical Society. 32(6). 2113–2116. 1 indexed citations
12.
Chung, Kee‐Choo, et al.. (2011). Convection Effects on PGSE-NMR Self-Diffusion Measurements at Low Temperature: Investigation into Sources of Induced Convective Flows. Bulletin of the Korean Chemical Society. 32(6). 1970–1974. 15 indexed citations
13.
Chung, Kee‐Choo, et al.. (2010). Modelling the effect of structural QSAR parameters on skin penetration using genetic programming. Advances in Natural Sciences Nanoscience and Nanotechnology. 1(3). 35003–35003. 3 indexed citations
14.
Cho, Jee‐Hyun, Sangdoo Ahn, Kwan Soo Hong, et al.. (2007). Magnetic resonance microscopic imaging based on high-order intermolecular multiple-quantum coherences. Magnetic Resonance Imaging. 25(5). 626–633. 7 indexed citations
15.
Chung, Kee‐Choo. (2007). Conformational Characteristics of Free and Cesium Complexed p-H-Calix[6]arene Alkyl Ester Derivatives. Bulletin of the Korean Chemical Society. 28(10). 1871–1873. 4 indexed citations
16.
Song, Ki Cheol, et al.. (2006). Fluorogenic Hg2+-Selective Chemodosimeter Derived from 8-Hydroxyquinoline. Organic Letters. 8(16). 3413–3416. 253 indexed citations
17.
Chung, Kee‐Choo. (2004). An NMR Study on Complexation of Cesium Ion by p-tert-Butylcalix[6]arene Ethyl Ester. Bulletin of the Korean Chemical Society. 25(5). 609–616. 2 indexed citations
18.
19.
Metlushko, V., U. Welp, G. W. Crabtree, et al.. (1999). Nonlinear flux-line dynamics in vanadium films with square lattices of submicron holes. Physical review. B, Condensed matter. 59(1). 603–607. 62 indexed citations
20.
Metlushko, V., U. Welp, G. W. Crabtree, et al.. (1999). Interstitial flux phases in a superconducting niobium film with a square lattice of artificial pinning centers. Physical review. B, Condensed matter. 60(18). R12585–R12588. 111 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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