Yejun Tan

2.1k total citations · 2 hit papers
37 papers, 1.7k citations indexed

About

Yejun Tan is a scholar working on Molecular Biology, Physiology and Epidemiology. According to data from OpenAlex, Yejun Tan has authored 37 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Molecular Biology, 12 papers in Physiology and 5 papers in Epidemiology. Recurrent topics in Yejun Tan's work include Alzheimer's disease research and treatments (5 papers), Adipose Tissue and Metabolism (5 papers) and Fibroblast Growth Factor Research (4 papers). Yejun Tan is often cited by papers focused on Alzheimer's disease research and treatments (5 papers), Adipose Tissue and Metabolism (5 papers) and Fibroblast Growth Factor Research (4 papers). Yejun Tan collaborates with scholars based in United States, China and Australia. Yejun Tan's co-authors include Michael J. Comb, John Rouse, Philip Cohen, Linda A. Kobierski, Hung Chu, Eric S. Muise, John R. Thompson, Joel P. Berger, Kenny K. Wong and Weijun Peng and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The EMBO Journal and Molecular and Cellular Biology.

In The Last Decade

Yejun Tan

35 papers receiving 1.6k citations

Hit Papers

FGF and stress regulate CREB and ATF-1 via a pathway invo... 1996 2026 2006 2016 1996 2024 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yejun Tan United States 16 1.1k 247 205 189 164 37 1.7k
Irina N. Gaisina United States 23 931 0.8× 270 1.1× 211 1.0× 141 0.7× 135 0.8× 59 1.6k
Yasuko Kitagishi Japan 23 1.0k 0.9× 299 1.2× 188 0.9× 241 1.3× 160 1.0× 55 1.9k
Kaori Nishikawa Japan 23 841 0.7× 259 1.0× 248 1.2× 167 0.9× 151 0.9× 44 1.7k
Nabil Hajji United Kingdom 19 1.1k 1.0× 262 1.1× 184 0.9× 228 1.2× 219 1.3× 36 2.0k
Christophe Vandier France 28 1.6k 1.4× 221 0.9× 384 1.9× 195 1.0× 137 0.8× 87 2.3k
Hee Sun Byun South Korea 20 757 0.7× 162 0.7× 141 0.7× 180 1.0× 114 0.7× 38 1.2k
Zhiyong Gao United States 27 985 0.9× 245 1.0× 156 0.8× 260 1.4× 248 1.5× 49 1.9k
Qidong Hu Singapore 16 1.0k 0.9× 162 0.7× 121 0.6× 192 1.0× 73 0.4× 20 1.7k
Alfredo Giménez-Cassina Spain 21 979 0.9× 382 1.5× 314 1.5× 125 0.7× 108 0.7× 29 1.5k
Liang Tao China 24 1.0k 0.9× 156 0.6× 125 0.6× 227 1.2× 111 0.7× 86 1.7k

Countries citing papers authored by Yejun Tan

Since Specialization
Citations

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

Fields of papers citing papers by Yejun Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yejun Tan

This figure shows the co-authorship network connecting the top 25 collaborators of Yejun Tan. A scholar is included among the top collaborators of Yejun Tan 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 Yejun Tan. Yejun Tan 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.
Chang, Sungwon, Yongyao Jiang, Tianlong Huang, et al.. (2025). Anxiety and depression in only children versus children with siblings: A cross-sectional study among Chinese medical students. Public Health. 239. 162–168. 2 indexed citations
2.
Zhang, Xinge, Chuiguo Huang, Yejun Tan, et al.. (2025). Global, regional, and country-specific lifetime risks of osteoarthritis, 1990–2021: a systematic analysis for the global burden of disease study 2021. Global Health Research and Policy. 10(1). 29–29. 1 indexed citations
3.
Peng, Weijun, Die Xu, Xiaowei Wang, et al.. (2025). Identification of Bruceine A as a novel HSP90AB1 inhibitor for suppressing hepatocellular carcinoma growth. Journal of Advanced Research. 82. 863–879. 1 indexed citations
4.
6.
Zheng, Qi, et al.. (2024). Over Activation of IL-6/STAT3 Signaling Pathway in Juvenile Dermatomyositis. Rheumatology and Therapy. 11(5). 1255–1269. 3 indexed citations
7.
Cheng, Xin, Yejun Tan, Hongli Li, et al.. (2024). Mechanistic Insights and Potential Therapeutic Implications of NRF2 in Diabetic Encephalopathy. Molecular Neurobiology. 61(10). 8253–8278. 4 indexed citations
8.
Liu, Yuqing, Yejun Tan, Zheyu Zhang, et al.. (2024). The interaction between ageing and Alzheimer's disease: insights from the hallmarks of ageing. Translational Neurodegeneration. 13(1). 7–7. 51 indexed citations breakdown →
9.
Tan, Yejun, et al.. (2023). Zingerone attenuates Ti particle-induced inflammatory osteolysis by suppressing the NF-κB signaling pathway in osteoclasts. International Immunopharmacology. 115. 109720–109720. 3 indexed citations
10.
Tan, Yejun, Wang Tang, Wenbiao Xiao, et al.. (2023). lncRNA-associated ceRNA network revealing the potential regulatory roles of ferroptosis and immune infiltration in Alzheimer’s disease. Frontiers in Aging Neuroscience. 15. 1105690–1105690. 10 indexed citations
11.
Tan, Yejun, Hongli Li, Aifang Zhong, et al.. (2023). Diabetes mellitus induces a novel inflammatory network involving cancer progression: Insights from bioinformatic analysis and in vitro validation. Frontiers in Immunology. 14. 1149810–1149810. 4 indexed citations
12.
Liu, Yuqing, Hongli Li, Xiaowei Wang, et al.. (2023). Anti-Alzheimers molecular mechanism of icariin: insights from gut microbiota, metabolomics, and network pharmacology. Journal of Translational Medicine. 21(1). 277–277. 80 indexed citations
13.
Liu, Yuqing, Yejun Tan, Zheyu Zhang, et al.. (2022). Neuroimmune mechanisms underlying Alzheimer’s disease: Insights into central and peripheral immune cell crosstalk. Ageing Research Reviews. 84. 101831–101831. 15 indexed citations
15.
Huang, Tao, Lei Liu, Qi Liu, et al.. (2011). The role of Hepatitis C Virus in the dynamic protein interaction networks of hepatocellular cirrhosis and carcinoma. International Journal of Computational Biology and Drug Design. 4(1). 5–5. 15 indexed citations
17.
Kamal, Mohammad Amjad, Yejun Tan, J. Paul Seale, & Xianqin Qu. (2009). Targeting BuChE-inflammatory Pathway by SK0506 to Manage Type 2 Diabetes and Alzheimer Disease. Neurochemical Research. 34(12). 2163–2169. 19 indexed citations
18.
Muise, Eric S., B. Azzolina, Mohamed El-Sherbeini, et al.. (2008). Adipose Fibroblast Growth Factor 21 Is Up-Regulated by Peroxisome Proliferator-Activated Receptor γ and Altered Metabolic States. Molecular Pharmacology. 74(2). 403–412. 245 indexed citations
19.
Chang, Ching H., Lesley A. McNamara, Margaret Wu, et al.. (2008). A novel selective peroxisome proliferator-activator receptor-γ modulator—SPPARγM5 improves insulin sensitivity with diminished adverse cardiovascular effects. European Journal of Pharmacology. 584(1). 192–201. 25 indexed citations
20.
Tan, Yejun, et al.. (2000). Complex Formation between Chromatium vinosum Ferric Cytochrome c′ and Bromophenol Blue. Archives of Biochemistry and Biophysics. 378(1). 40–44. 11 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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