Jae Hun Cheong

922 total citations
9 papers, 782 citations indexed

About

Jae Hun Cheong is a scholar working on Molecular Biology, Cancer Research and Genetics. According to data from OpenAlex, Jae Hun Cheong has authored 9 papers receiving a total of 782 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 4 papers in Cancer Research and 3 papers in Genetics. Recurrent topics in Jae Hun Cheong's work include Retinoids in leukemia and cellular processes (4 papers), Estrogen and related hormone effects (3 papers) and NF-κB Signaling Pathways (3 papers). Jae Hun Cheong is often cited by papers focused on Retinoids in leukemia and cellular processes (4 papers), Estrogen and related hormone effects (3 papers) and NF-κB Signaling Pathways (3 papers). Jae Hun Cheong collaborates with scholars based in South Korea, Japan and United States. Jae Hun Cheong's co-authors include Seishi Murakami, Yong Lin, Min Yi, Jae Woon Lee, Soo‐Kyung Lee, Young Chul Lee, Takaji Wakita, Chul‐Yong Park, Soon B. Hwang and Jeffrey M. Trent and has published in prestigious journals such as Journal of Biological Chemistry, The EMBO Journal and Biochemical Journal.

In The Last Decade

Jae Hun Cheong

8 papers receiving 774 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jae Hun Cheong South Korea 8 460 240 181 143 142 9 782
Sylvie Prigent France 13 469 1.0× 210 0.9× 69 0.4× 86 0.6× 133 0.9× 17 756
Hyo-Jong Kim South Korea 11 783 1.7× 120 0.5× 143 0.8× 186 1.3× 191 1.3× 11 1.1k
Weihua Xu China 16 724 1.6× 122 0.5× 67 0.4× 291 2.0× 147 1.0× 44 1.1k
Johnny Loke United States 10 425 0.9× 273 1.1× 107 0.6× 57 0.4× 50 0.4× 16 842
SHENG-CHUNG LEE Taiwan 11 567 1.2× 49 0.2× 89 0.5× 164 1.1× 132 0.9× 12 852
Shwu‐Yuan Wu United States 11 739 1.6× 165 0.7× 160 0.9× 66 0.5× 201 1.4× 16 958
Buyun Ma China 14 265 0.6× 80 0.3× 116 0.6× 97 0.7× 130 0.9× 25 518
Hongxin Zhang China 16 394 0.9× 72 0.3× 52 0.3× 99 0.7× 88 0.6× 33 561
Yuichiro Amano Japan 14 544 1.2× 109 0.5× 69 0.4× 42 0.3× 74 0.5× 31 820
Mohd Jamal Dar India 13 496 1.1× 87 0.4× 52 0.3× 62 0.4× 69 0.5× 27 720

Countries citing papers authored by Jae Hun Cheong

Since Specialization
Citations

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

Fields of papers citing papers by Jae Hun Cheong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jae Hun Cheong. 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 Jae Hun Cheong. The network helps show where Jae Hun Cheong may publish in the future.

Co-authorship network of co-authors of Jae Hun Cheong

This figure shows the co-authorship network connecting the top 25 collaborators of Jae Hun Cheong. A scholar is included among the top collaborators of Jae Hun Cheong 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 Jae Hun Cheong. Jae Hun Cheong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
1.
Zhang, Jian, Ting Le, Yeon-Ju Kim, et al.. (2021). Dronedarone hydrochloride enhances the bioactivity of endothelial progenitor cells via regulation of the AKT signaling pathway. Korean Journal of Physiology and Pharmacology. 25(5). 459–466.
2.
Hwangbo, Hyun, Won Sup Lee, Arulkumar Nagappan, et al.. (2019). Morin enhances auranofin anticancer activity by up‐regulation of DR4 and DR5 and modulation of Bcl‐2 through reactive oxygen species generation in Hep3B human hepatocellular carcinoma cells. Phytotherapy Research. 33(5). 1384–1393. 23 indexed citations
3.
Park, Chul‐Yong, et al.. (2009). Hepatitis C Virus Nonstructural 4B Protein Modulates Sterol Regulatory Element-binding Protein Signaling via the AKT Pathway. Journal of Biological Chemistry. 284(14). 9237–9246. 112 indexed citations
4.
Park, Min Jung, et al.. (2007). Transcriptional repression of the gluconeogenic gene PEPCK by the orphan nuclear receptor SHP through inhibitory interaction with C/EBPα. Biochemical Journal. 402(3). 567–574. 33 indexed citations
5.
Kong, Hee Jeong, et al.. (2003). Interaction and functional cooperation of the cancer-amplified transcriptional coactivator activating signal cointegrator-2 and E2F-1 in cell proliferation.. PubMed. 1(13). 948–58. 19 indexed citations
6.
Jang, Moon Kyoo, Young Chang Sohn, Soo‐Kyung Lee, et al.. (2001). Ca2+/Calmodulin-dependent Protein Kinase IV Stimulates Nuclear Factor-κB Transactivation via Phosphorylation of the p65 Subunit. Journal of Biological Chemistry. 276(23). 20005–20010. 71 indexed citations
8.
Lee, Soo‐Kyung, Sarah L. Anzick, Ji Eun Choi, et al.. (1999). A Nuclear Factor, ASC-2, as a Cancer-amplified Transcriptional Coactivator Essential for Ligand-dependent Transactivation by Nuclear Receptors in Vivo. Journal of Biological Chemistry. 274(48). 34283–34293. 184 indexed citations
9.
Cheong, Jae Hun, Min Yi, Yong Lin, & Seishi Murakami. (1995). Human RPB5, a subunit shared by eukaryotic nuclear RNA polymerases, binds human hepatitis B virus X protein and may play a role in X transactivation.. The EMBO Journal. 14(1). 143–150. 226 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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