Jun Yin
Impact in
- Physiology top 0.5%
- Adipose Tissue and Metabolism
- Diet and metabolism studies
- Pharmacology top 0.5%
- Berberine and alkaloids research
Papers in
-
- Diet, Metabolism, and Disease 6
- Diabetes Treatment and Management 5
- Physiology 24
- Adipose Tissue and Metabolism 14
- Diet and metabolism studies 7
- Co-authors
- Jianping YeZhan‐Guo GaoQing HeRoy J. MartinJin ZhangWilliam T. CefaluMichael LefevreRobert E. Ward
- Journals
- American Journal of Physiology-Endocrinology and Metabolism (7 papers)Journal of Biological Chemistry (6 papers)PLoS ONE (6 papers)Scientific Reports (3 papers)Metabolism (3 papers)
- Partner nations
- ChinaUnited StatesIndia
In The Last Decade
Jun Yin
87 papers receiving 6.8k citations
Hit Papers
Peers
Comparison fields: 5 of 135
- Physiology 2.5k
- Pharmacology 1.3k
- Endocrinology, Diabetes and Metabolism 1.1k
- Geriatrics and Gerontology 250
- Pharmacology 548
Countries citing papers authored by Jun Yin
This map shows the geographic impact of Jun Yin'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 Jun Yin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Yin more than expected).
Fields of papers citing papers by Jun Yin
This network shows the impact of papers produced by Jun Yin. 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 Jun Yin. The network helps show where Jun Yin may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jun Yin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 3 | |
| 3 | 2024 | 4 | |
| 4 | 2023 | 8 | |
| 5 | 2023 | 17 | |
| 6 | 2022 | 5 | |
| 7 | 2021 | 24 | |
| 8 | 2021 | 7 | |
| 9 | 2021 | 18 | |
| 10 | 2020 | 84 | |
| 11 | 2019 | 4 | |
| 12 | 2018 | 31 | |
| 13 | 2018 | 21 | |
| 14 | 2018 | 69 | |
| 15 | 2015 | 31 | |
| 16 | 2013 | 14 | |
| 17 | Butyrate Improves Insulin Sensitivity and Increases Energy Expenditure in Mice Hit paper breakdown → | 2009 | 1707 |
| 18 | 2008 | 316 | |
| 19 | 2008 | 179 | |
| 20 | 2006 | 62 |
About Jun Yin
Jun Yin is a scholar working on Endocrinology, Diabetes and Metabolism, Physiology, Pharmacology, Molecular Biology and Clinical Biochemistry, having authored 90 papers that have together received 6.9k indexed citations. Recurring topics across this work include Metabolism, Diabetes, and Cancer (18 papers), Adipose Tissue and Metabolism (14 papers), Pancreatic function and diabetes (11 papers), Diet and metabolism studies (7 papers), Berberine and alkaloids research (7 papers), Adipokines, Inflammation, and Metabolic Diseases (7 papers), Diet, Metabolism, and Disease (6 papers) and Diabetes Treatment and Management (5 papers). The work is most often cited by research in Physiology (2.5k citations), Pharmacology (1.3k citations), Endocrinology, Diabetes and Metabolism (1.1k citations), Geriatrics and Gerontology (250 citations) and Pharmacology (548 citations). Jun Yin has collaborated with scholars based in China, United States and India. Frequent co-authors include Jianping Ye, Zhan‐Guo Gao, Qing He, Roy J. Martin, Jin Zhang, William T. Cefalu, Michael Lefevre, Robert E. Ward, Xing Hui-li and Weiping Jia. Their work appears in journals such as American Journal of Physiology-Endocrinology and Metabolism, Journal of Biological Chemistry, PLoS ONE, Scientific Reports and Metabolism.
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.