Jongseon Choe

4.0k total citations
104 papers, 3.4k citations indexed

About

Jongseon Choe is a scholar working on Immunology, Molecular Biology and Cancer Research. According to data from OpenAlex, Jongseon Choe has authored 104 papers receiving a total of 3.4k indexed citations (citations by other indexed papers that have themselves been cited), including 53 papers in Immunology, 44 papers in Molecular Biology and 25 papers in Cancer Research. Recurrent topics in Jongseon Choe's work include Immunotherapy and Immune Responses (31 papers), T-cell and B-cell Immunology (23 papers) and Immune Cell Function and Interaction (22 papers). Jongseon Choe is often cited by papers focused on Immunotherapy and Immune Responses (31 papers), T-cell and B-cell Immunology (23 papers) and Immune Cell Function and Interaction (22 papers). Jongseon Choe collaborates with scholars based in South Korea, United States and United Kingdom. Jongseon Choe's co-authors include Dooil Jeoung, Hansoo Lee, Young‐Myeong Kim, Yong Sung Choi, Kwon‐Soo Ha, Youngmi Kim, Yun‐Sil Lee, Deokbum Park, In Yong Lee and Young‐Guen Kwon and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and SHILAP Revista de lepidopterología.

In The Last Decade

Jongseon Choe

101 papers receiving 3.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jongseon Choe South Korea 35 1.4k 1.4k 533 473 241 104 3.4k
Zhixing K. Pan United States 36 1.3k 0.9× 1.6k 1.2× 742 1.4× 668 1.4× 112 0.5× 61 3.3k
Włodzimierz Maśliński Poland 35 1.8k 1.3× 1.4k 1.0× 319 0.6× 656 1.4× 204 0.8× 150 4.4k
Suk‐Hwan Baek South Korea 33 836 0.6× 1.6k 1.1× 390 0.7× 364 0.8× 188 0.8× 92 3.0k
Chang-Hoon Woo South Korea 34 719 0.5× 1.4k 1.0× 416 0.8× 315 0.7× 125 0.5× 53 2.6k
Claus Johansen Denmark 35 2.2k 1.5× 1.3k 0.9× 558 1.0× 727 1.5× 119 0.5× 115 3.7k
Onno J. Arntz Netherlands 34 873 0.6× 1.5k 1.1× 720 1.4× 670 1.4× 436 1.8× 75 3.5k
Ryuhei Okuyama Japan 31 1.2k 0.9× 1.3k 0.9× 355 0.7× 1.2k 2.6× 146 0.6× 164 3.7k
Mayumi Fujita United States 34 1.4k 1.0× 1.9k 1.4× 425 0.8× 1.0k 2.2× 121 0.5× 131 4.1k
Gernot Schabbauer Austria 34 1.3k 0.9× 1.5k 1.1× 402 0.8× 394 0.8× 154 0.6× 76 3.5k
Serafim Kiriakidis United Kingdom 26 739 0.5× 965 0.7× 674 1.3× 416 0.9× 133 0.6× 42 2.6k

Countries citing papers authored by Jongseon Choe

Since Specialization
Citations

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

Fields of papers citing papers by Jongseon Choe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jongseon Choe

This figure shows the co-authorship network connecting the top 25 collaborators of Jongseon Choe. A scholar is included among the top collaborators of Jongseon Choe 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 Jongseon Choe. Jongseon Choe 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.
Han, Eun‐Taek, Won Sun Park, Jin‐Hee Han, et al.. (2025). Computational Analysis of GAT1 Mutations: Functional Consequences from Molecular Dynamics and Binding Free Energy Calculations. International Journal of Molecular Sciences. 26(23). 11339–11339. 1 indexed citations
2.
Yasir, Muhammad, Jongseon Choe, Jin‐Hee Han, & Wanjoo Chun. (2025). Molecular Basis of GABA Aminotransferase Inhibition in Epilepsy: Structure, Mechanisms, and Drug Development. Current Issues in Molecular Biology. 47(12). 1032–1032.
3.
Han, Eun‐Taek, et al.. (2025). Integration of Deep Learning with Molecular Docking and Molecular Dynamics Simulation for Novel TNF-α-Converting Enzyme Inhibitors. SHILAP Revista de lepidopterología. 5(4). 55–55. 2 indexed citations
4.
Jeong, Jihye & Jongseon Choe. (2023). Akt, IL-4, and STAT Proteins Play Distinct Roles in Prostaglandin Production in Human Follicular Dendritic Cell-like Cells. International Journal of Molecular Sciences. 24(23). 16692–16692. 1 indexed citations
5.
Choe, Jongseon, et al.. (2020). A paracrine effect of 15 (S)-hydroxyeicosatetraenoic acid revealed in prostaglandin production by human follicular dendritic cell-like cells. Prostaglandins & Other Lipid Mediators. 151. 106487–106487. 2 indexed citations
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Lee, Seungkoo, et al.. (2017). Activated human B cells stimulate COX-2 expression in follicular dendritic cell-like cells via TNF-α. Molecular Immunology. 94. 1–6. 9 indexed citations
9.
Kim, Youngmi, Hyuna Kim, Deokbum Park, et al.. (2016). miR-217 and CAGE form feedback loop and regulates the response to anti-cancer drugs through EGFR and HER2. Oncotarget. 7(9). 10297–10321. 20 indexed citations
10.
Choe, Jongseon, Ji-Hoon Park, Seungkoo Lee, Young‐Myeong Kim, & Dooil Jeoung. (2016). Opposing roles of TGF-β in prostaglandin production by human follicular dendritic cell-like cells. Molecular Immunology. 76. 41–48. 4 indexed citations
11.
Jeoung, Dooil, et al.. (2015). Interferon-γ stimulates human follicular dendritic cell-like cells to produce prostaglandins via the JAK-STAT pathway. Molecular Immunology. 66(2). 189–196. 14 indexed citations
12.
Kim, Jihee, Kwang-Soon Lee, Dong-Keon Lee, et al.. (2014). Hypoxia-Responsive MicroRNA-101 Promotes Angiogenesis via Heme Oxygenase-1/Vascular Endothelial Growth Factor Axis by Targeting Cullin 3. Antioxidants and Redox Signaling. 21(18). 2469–2482. 74 indexed citations
13.
Kim, Youngmi, Hyuna Kim, Hyunmi Park, et al.. (2014). miR-326-Histone Deacetylase-3 Feedback Loop Regulates the Invasion and Tumorigenic and Angiogenic Response to Anti-cancer Drugs. Journal of Biological Chemistry. 289(40). 28019–28039. 37 indexed citations
14.
Lee, Seungkoo, et al.. (2013). Human follicular dendritic cells promote germinal center B cell survival by providing prostaglandins. Molecular Immunology. 55(3-4). 418–423. 17 indexed citations
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16.
Kim, Ji‐Hee, Young-Lai Cho, CK Kim, et al.. (2008). Desmethylanhydroicaritin inhibits NF-κB-regulated inflammatory gene expression by modulating the redox-sensitive PI3K/PTEN/Akt pathway. European Journal of Pharmacology. 602(2-3). 422–431. 32 indexed citations
17.
Lee, In Yong, et al.. (2005). Human Follicular Dendritic Cells Express Prostacyclin Synthase: A Novel Mechanism to Control T Cell Numbers in the Germinal Center. The Journal of Immunology. 175(3). 1658–1664. 29 indexed citations
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Lee, In Yong & Jongseon Choe. (2003). Human follicular dendritic cells and fibroblasts share the 3C8 antigen. Biochemical and Biophysical Research Communications. 304(4). 701–707. 37 indexed citations
20.
Jung, Jaeho, Ae‐Kyung Yi, Xin Zhang, et al.. (2002). Distinct Response of Human B Cell Subpopulations in Recognition of an Innate Immune Signal, CpG DNA. The Journal of Immunology. 169(5). 2368–2373. 54 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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