John Y. Jun

1.8k citations
23 papers · 1.3k · h-index 13

Impact in

    • Adipokines, Inflammation, and Metabolic Diseases
    • Liver Disease Diagnosis and Treatment
  • Physiology top 5%
    • Adipose Tissue and Metabolism

Papers in

John Y. Jun

21 papers receiving 1.3k citations

Peers

John Y. Jun
Comparison fields: 5 of 85
  • Epidemiology 521
  • Physiology 353
  • Endocrine and Autonomic Systems 87
  • Cell Biology 209
  • Endocrinology, Diabetes and Metabolism 172
Replace Changhua Wang with:
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Heekyung Chung United States
Takamasa Higashimori United States
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John Y. Jun relative to Changhua Wang China Changhua Wang's profile →
Citations per field
00.5×1.5×2.1×
Changhua Wang · 1×
Citations per year

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-authors

The 25 scholars most cited alongside John Y. Jun, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with John Y. Jun Line = papers co-authored together John Y. Jun links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008492
2 2009149
3 2009128
4 2009125
5 201260
6 200758
7 201355
8 201054
9 201146
10 201637
11 201136
12 201229
13 201023
14 200710
15 202010
16 202010
17 202510
18 20065
19 20183
20 20252

About John Y. Jun

John Y. Jun is a scholar working on Molecular Biology, Endocrinology, Diabetes and Metabolism, Surgery, Endocrine and Autonomic Systems and Epidemiology, having authored 23 papers that have together received 1.3k indexed citations. Recurring topics across this work include Pancreatic function and diabetes (3 papers), Diabetes and associated disorders (2 papers), Endoplasmic Reticulum Stress and Disease (2 papers), Amino Acid Enzymes and Metabolism (2 papers), Metabolism, Diabetes, and Cancer (2 papers), Diabetes Treatment and Management (2 papers), Adipose Tissue and Metabolism (2 papers) and Epigenetics and DNA Methylation (2 papers). The work is most often cited by research in Epidemiology (521 citations), Physiology (353 citations), Endocrine and Autonomic Systems (87 citations), Cell Biology (209 citations) and Endocrinology, Diabetes and Metabolism (172 citations). John Y. Jun has collaborated with scholars based in United States, Australia and Egypt. Frequent co-authors include Jason K. Kim, Hwi Jin Ko, Zhiyou Zhang, Guadalupe Sabio, Tamera Barrett, Roger J. Davis, Alfonso Mora, Dae Young Jung, Madhumita Das and Lakshman Segar. Their work appears in journals such as Diabetes, American Journal of Physiology-Endocrinology and Metabolism, Breast Cancer Research and Treatment, American Journal of Physiology-Cell Physiology and Otolaryngologic Clinics of North America.

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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