John Y. Jun

1.7k total citations
23 papers, 1.3k citations indexed

About

John Y. Jun is a scholar working on Surgery, Molecular Biology and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, John Y. Jun has authored 23 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Surgery, 9 papers in Molecular Biology and 7 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in John Y. Jun's work include Pancreatic function and diabetes (7 papers), Adipose Tissue and Metabolism (5 papers) and Adipokines, Inflammation, and Metabolic Diseases (5 papers). John Y. Jun is often cited by papers focused on Pancreatic function and diabetes (7 papers), Adipose Tissue and Metabolism (5 papers) and Adipokines, Inflammation, and Metabolic Diseases (5 papers). John Y. Jun collaborates with scholars based in United States, Australia and Egypt. John Y. Jun's co-authors include Jason K. Kim, Hwi Jin Ko, Zhiyou Zhang, Tamera Barrett, Alfonso Mora, Roger J. Davis, Guadalupe Sabio, Dae Young Jung, Madhumita Das and Lakshman Segar and has published in prestigious journals such as Science, Cell Metabolism and Diabetes.

In The Last Decade

John Y. Jun

20 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
John Y. Jun United States 13 582 540 403 247 223 23 1.3k
Sung‐E Choi South Korea 22 450 0.8× 694 1.3× 352 0.9× 322 1.3× 216 1.0× 53 1.6k
Diana M. Willmes Germany 14 391 0.7× 839 1.6× 380 0.9× 224 0.9× 184 0.8× 17 1.5k
Sarah M. Turpin-Nolan Australia 11 464 0.8× 1.0k 1.9× 687 1.7× 263 1.1× 259 1.2× 16 1.7k
Marthe Moldes France 24 659 1.1× 1.1k 2.0× 510 1.3× 365 1.5× 236 1.1× 40 2.1k
Joshua E. Basford United States 19 344 0.6× 479 0.9× 314 0.8× 260 1.1× 95 0.4× 22 1.2k
Blas A. Guigni United States 16 551 0.9× 539 1.0× 453 1.1× 233 0.9× 182 0.8× 19 1.3k
Chunjiong Wang China 19 432 0.7× 513 0.9× 236 0.6× 250 1.0× 183 0.8× 26 1.4k
Angela M. Siesky United States 8 326 0.6× 816 1.5× 531 1.3× 225 0.9× 190 0.9× 8 1.3k
Banumathi K. Cole United States 20 522 0.9× 580 1.1× 283 0.7× 273 1.1× 277 1.2× 26 1.7k
Midori Fujishiro Japan 15 383 0.7× 706 1.3× 478 1.2× 222 0.9× 86 0.4× 22 1.5k

Countries citing papers authored by John Y. Jun

Since Specialization
Citations

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

Fields of papers citing papers by John Y. Jun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John Y. Jun. 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 John Y. Jun. The network helps show where John Y. Jun may publish in the future.

Co-authorship network of co-authors of John Y. Jun

This figure shows the co-authorship network connecting the top 25 collaborators of John Y. Jun. A scholar is included among the top collaborators of John Y. Jun 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 John Y. Jun. John Y. Jun 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.
2.
Paparodis, Rodis, Asif Mahmood, John Y. Jun, et al.. (2025). Conversion of T Effector Cells Into T Regulatory Cells in Type 1 Diabetes/Latent Autoimmune Diabetes of Adults by Inhibiting eIF5A and Notch Pathways. ImmunoTargets and Therapy. Volume 14. 205–226.
3.
Dewan, Syed Masudur Rahman, et al.. (2024). 7209 Immune Check Point Inhibitors And Periodic Thyroid Function Assessment. Journal of the Endocrine Society. 8(Supplement_1).
4.
Taftaf, Rokana, et al.. (2023). Aldosterone- and Cortisol Co-secreting Adrenal Cortical Neoplasm With Lipomatous and Myelolipomatous Metaplasia  . JCEM Case Reports. 1(2). luad012–luad012.
5.
Pichavaram, Prahalathan, et al.. (2020). Imatinib improves insulin resistance and inhibits injury-induced neointimal hyperplasia in high fat diet-fed mice. European Journal of Pharmacology. 890. 173666–173666. 8 indexed citations
6.
Lee, Sanghoon, et al.. (2020). WNT Signaling Driven by R-spondin 1 and LGR6 in High-grade Serous Ovarian Cancer. Anticancer Research. 40(11). 6017–6028. 10 indexed citations
7.
Jaume, Juan Carlos, et al.. (2018). Locally Invasive Pheochromocytoma Combined with Primary Malignant Adrenal Lymphoma. AACE Clinical Case Reports. 5(2). e124–e128. 3 indexed citations
8.
Shawky, Noha M., Prahalathan Pichavaram, George S.G. Shehatou, et al.. (2016). Sulforaphane improves dysregulated metabolic profile and inhibits leptin-induced VSMC proliferation: Implications toward suppression of neointima formation after arterial injury in western diet-fed obese mice. The Journal of Nutritional Biochemistry. 32. 73–84. 37 indexed citations
9.
Poulose, Ninu, et al.. (2013). Expression of conventional and novel glucose transporters, GLUT1, -9, -10, and -12, in vascular smooth muscle cells. American Journal of Physiology-Cell Physiology. 304(6). C574–C589. 55 indexed citations
10.
11.
Zhang, Zhiyou, Wenyi Zhang, Dae Young Jung, et al.. (2012). TRPM2 Ca2+ channel regulates energy balance and glucose metabolism. American Journal of Physiology-Endocrinology and Metabolism. 302(7). E807–E816. 57 indexed citations
12.
Zhao, Yan, Swarajit Kumar Biswas, Patrick H. McNulty, et al.. (2011). PDGF-induced vascular smooth muscle cell proliferation is associated with dysregulation of insulin receptor substrates. American Journal of Physiology-Cell Physiology. 300(6). C1375–C1385. 43 indexed citations
13.
Jun, John Y., Zhexi Ma, & Lakshman Segar. (2011). Spontaneously diabetic Ins2+/Akita:apoE-deficient mice exhibit exaggerated hypercholesterolemia and atherosclerosis. American Journal of Physiology-Endocrinology and Metabolism. 301(1). E145–E154. 36 indexed citations
14.
Sabio, Guadalupe, Julie Cavanagh-Kyros, Hwi Jin Ko, et al.. (2009). Prevention of Steatosis by Hepatic JNK1. Cell Metabolism. 10(6). 491–498. 125 indexed citations
15.
Ye, Risheng, Dae Young Jung, John Y. Jun, et al.. (2009). Grp78 Heterozygosity Promotes Adaptive Unfolded Protein Response and Attenuates Diet-Induced Obesity and Insulin Resistance. Diabetes. 59(1). 6–16. 148 indexed citations
16.
Sabio, Guadalupe, Madhumita Das, Alfonso Mora, et al.. (2008). A Stress Signaling Pathway in Adipose Tissue Regulates Hepatic Insulin Resistance. Science. 322(5907). 1539–1543. 491 indexed citations
17.
Jun, John Y. & Andrea Manni. (2008). Medical Management of Persistent or Recurrent Differentiated Thyroid Carcinoma. Otolaryngologic Clinics of North America. 41(6). 1241–1260. 1 indexed citations
18.
Jun, John Y., James W. Griffith, Richard Bruggeman, et al.. (2007). Effects of polyamine depletion by α-difluoromethylornithine on in vitro and in vivo biological properties of 4T1 murine mammary cancer cells. Breast Cancer Research and Treatment. 107(1). 33–40. 10 indexed citations
19.
Hong, Eun‐Gyoung, Dae Young Jung, Hwi Jin Ko, et al.. (2007). Nonobese, insulin-deficient Ins2Akitamice develop type 2 diabetes phenotypes including insulin resistance and cardiac remodeling. American Journal of Physiology-Endocrinology and Metabolism. 293(6). E1687–E1696. 57 indexed citations
20.
Jun, John Y., James W. Griffith, Richard Bruggeman, et al.. (2006). Effects of polyamine depletion by α-difluoromethylornithine on in vitro and in vivo biological properties of 4T1 murine mammary cancer cells. Breast Cancer Research and Treatment. 105(1). 29–36. 5 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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