Ung‐il Chung

21.5k total citations · 4 hit papers
317 papers, 17.5k citations indexed

About

Ung‐il Chung is a scholar working on Molecular Biology, Rheumatology and Biomedical Engineering. According to data from OpenAlex, Ung‐il Chung has authored 317 papers receiving a total of 17.5k indexed citations (citations by other indexed papers that have themselves been cited), including 126 papers in Molecular Biology, 73 papers in Rheumatology and 68 papers in Biomedical Engineering. Recurrent topics in Ung‐il Chung's work include Hydrogels: synthesis, properties, applications (66 papers), Osteoarthritis Treatment and Mechanisms (60 papers) and Bone Metabolism and Diseases (46 papers). Ung‐il Chung is often cited by papers focused on Hydrogels: synthesis, properties, applications (66 papers), Osteoarthritis Treatment and Mechanisms (60 papers) and Bone Metabolism and Diseases (46 papers). Ung‐il Chung collaborates with scholars based in Japan, United States and Sweden. Ung‐il Chung's co-authors include Takamasa Sakai, Hiroshi Kawaguchi, Shinsuke Ohba, Kozo Nakamura, Yuki Akagi, Mitsuhiro Shibayama, Takuro Matsunaga, Satoru Kamekura, Henry M. Kronenberg and Taku Saito and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Physical Review Letters.

In The Last Decade

Ung‐il Chung

306 papers receiving 17.3k citations

Hit Papers

Design and Fabrication of a High-Strength Hydrogel with I... 2004 2026 2011 2018 2008 2004 2004 2014 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ung‐il Chung Japan 68 6.6k 3.7k 3.6k 3.2k 2.3k 317 17.5k
Marcel Karperien Netherlands 64 5.9k 0.9× 3.4k 0.9× 3.5k 1.0× 1.1k 0.4× 2.5k 1.0× 309 15.4k
Yasuhiko Tabata Japan 93 9.3k 1.4× 2.7k 0.7× 11.0k 3.1× 2.0k 0.6× 11.1k 4.7× 916 35.9k
Gang Li China 80 12.5k 1.9× 1.9k 0.5× 4.2k 1.2× 566 0.2× 2.4k 1.0× 1.1k 30.5k
Jianxun Ding China 84 5.6k 0.9× 1.4k 0.4× 10.5k 2.9× 1.9k 0.6× 10.3k 4.4× 359 22.6k
Mary C. Farach‐Carson United States 60 4.5k 0.7× 1.9k 0.5× 2.7k 0.8× 421 0.1× 1.6k 0.7× 237 12.1k
Robert F. Padera United States 65 3.9k 0.6× 1.0k 0.3× 3.4k 0.9× 507 0.2× 2.5k 1.1× 186 16.1k
Wenguang Liu China 80 3.9k 0.6× 665 0.2× 7.8k 2.2× 3.9k 1.2× 6.1k 2.6× 377 21.5k
Richard O. C. Oreffo United Kingdom 77 5.4k 0.8× 2.5k 0.7× 12.8k 3.6× 621 0.2× 4.9k 2.1× 393 22.9k
Yoshihiro Ito Japan 60 6.2k 0.9× 570 0.2× 4.2k 1.2× 706 0.2× 2.7k 1.1× 500 14.3k
Judith A. Hoyland United Kingdom 61 2.7k 0.4× 2.5k 0.7× 2.2k 0.6× 564 0.2× 1.0k 0.4× 201 13.0k

Countries citing papers authored by Ung‐il Chung

Since Specialization
Citations

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

Fields of papers citing papers by Ung‐il Chung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ung‐il Chung

This figure shows the co-authorship network connecting the top 25 collaborators of Ung‐il Chung. A scholar is included among the top collaborators of Ung‐il 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 Ung‐il Chung. Ung‐il 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.
Shinohara, Shuji, et al.. (2025). Simple modification of the upper confidence bound algorithm by generalized weighted averages. PLoS ONE. 20(5). e0322757–e0322757.
3.
Naito, Mitsuru, et al.. (2024). Predicting the effects of degradation on viscoelastic relaxation time using model transient networks. Polymer Journal. 56(7). 685–691. 1 indexed citations
4.
5.
Chung, Ung‐il, et al.. (2023). Probing the Molecular Mechanism of Viscoelastic Relaxation in Transient Networks. Gels. 9(12). 945–945. 4 indexed citations
6.
Kim, Junhyuk, et al.. (2023). Miscibility and ternary diagram of aqueous polyvinyl alcohols with different degrees of saponification. Scientific Reports. 13(1). 8791–8791. 1 indexed citations
7.
Uneyama, Takashi, Xiang Li, Hironori Hojo, et al.. (2023). Percolation-induced gel–gel phase separation in a dilute polymer network. Nature Materials. 22(12). 1564–1570. 32 indexed citations
8.
Svensson, Thomas, et al.. (2023). A Disentangled VAE-BiLSTM Model for Heart Rate Anomaly Detection. Bioengineering. 10(6). 683–683. 11 indexed citations
9.
Katashima, Takuya, R. Kudo, Mitsuru Naito, et al.. (2022). Experimental Comparison of Bond Lifetime and Viscoelastic Relaxation in Transient Networks with Well-Controlled Structures. ACS Macro Letters. 11(6). 753–759. 13 indexed citations
10.
Nakamura, Sho, et al.. (2022). Checking the validity and reliability of the Japanese version of the Mini-Cog using a smartphone application. BMC Research Notes. 15(1). 222–222. 1 indexed citations
11.
Svensson, Thomas, et al.. (2022). Sleep Satisfaction May Modify the Association between Metabolic Syndrome and BMI, Respectively, and Occupational Stress in Japanese Office Workers. International Journal of Environmental Research and Public Health. 19(9). 5095–5095. 3 indexed citations
12.
Svensson, Thomas, et al.. (2021). Associations of work-related stress and total sleep time with cholesterol levels in an occupational cohort of Japanese office workers. Journal of Occupational Health. 63(1). e12275–e12275. 4 indexed citations
13.
Shinohara, Shuji, et al.. (2021). Power Laws Derived from a Bayesian Decision-Making Model in Non-Stationary Environments. Symmetry. 13(4). 718–718. 1 indexed citations
14.
Shinohara, Shuji, et al.. (2020). A new method of Bayesian causal inference in non-stationary environments. PLoS ONE. 15(5). e0233559–e0233559. 3 indexed citations
15.
Svensson, Thomas, Akiko Kishi Svensson, Hirokazu Urushiyama, et al.. (2020). Using mHealth to Provide Mobile App Users With Visualization of Health Checkup Data and Educational Videos on Lifestyle-Related Diseases: Methodological Framework for Content Development. JMIR mhealth and uhealth. 8(10). e20982–e20982. 8 indexed citations
16.
Wu, Shourong, Vivi Kasim, Mitsunobu R. Kano, et al.. (2013). Transcription Factor YY1 Contributes to Tumor Growth by Stabilizing Hypoxia Factor HIF-1α in a p53-Independent Manner. Cancer Research. 73(6). 1787–1799. 67 indexed citations
17.
Fukai, Atsushi, Satoru Kamekura, Daichi Chikazu, et al.. (2011). Lack of a chondroprotective effect of cyclooxygenase 2 inhibition in a surgically induced model of osteoarthritis in mice. Arthritis & Rheumatism. 64(1). 198–203. 34 indexed citations
18.
Long, Fanxin, Ung‐il Chung, Shinsuke Ohba, et al.. (2004). Ihh signaling is directly required for the osteoblast lineage in the endochondral skeleton. Development. 131(6). 1309–1318. 341 indexed citations
19.
Akune, Toru, Shinsuke Ohba, Satoru Kamekura, et al.. (2004). PPAR γ insufficiency enhances osteogenesis through osteoblast formation from bone marrow progenitors. Journal of Clinical Investigation. 113(6). 846–855. 631 indexed citations breakdown →
20.
Akune, Toru, Shinsuke Ohba, Satoru Kamekura, et al.. (2004). PPAR γ insufficiency enhances osteogenesis through osteoblast formation from bone marrow progenitors. Journal of Clinical Investigation. 113(6). 846–855. 677 indexed citations breakdown →

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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