Junling Tang
Impact in
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- Diabetes, Cardiovascular Risks, and Lipoproteins
- Diabetes Management and Research
- Diabetes Treatment and Management
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- Bone health and osteoporosis research
Papers in
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- Diabetes, Cardiovascular Risks, and Lipoproteins 16
- Diabetes Management and Research 9
- Diabetes Treatment and Management 6
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- Gestational Diabetes Research and Management 4
Junling Tang
49 papers receiving 995 citations
Peers
Comparison fields: 5 of 97
- Endocrinology, Diabetes and Metabolism 417
- Orthopedics and Sports Medicine 142
- Obstetrics and Gynecology 120
- Nephrology 45
- Epidemiology 180
Countries citing papers authored by Junling Tang
This map shows the geographic impact of Junling Tang'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 Junling Tang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Junling Tang more than expected).
Fields of papers citing papers by Junling Tang
This network shows the impact of papers produced by Junling Tang. 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 Junling Tang. The network helps show where Junling Tang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Junling Tang, 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 | 2025 | 0 | |
| 3 | 2022 | 12 | |
| 4 | 2019 | 1 | |
| 5 | 2018 | 5 | |
| 6 | 2018 | 5 | |
| 7 | 2018 | 47 | |
| 8 | 2018 | 2 | |
| 9 | 2017 | 7 | |
| 10 | 2017 | 53 | |
| 11 | 2013 | 35 | |
| 12 | 2012 | 40 | |
| 13 | 2012 | 10 | |
| 14 | 2010 | 1 | |
| 15 | 2010 | 26 | |
| 16 | 2010 | 40 | |
| 17 | 2009 | 8 | |
| 18 | 2006 | 166 | |
| 19 | An association study of resting energy expenditure, total and regional body fat with the polymorphism of UCP2 gene | 2004 | 4 |
| 20 | [The association between A55V variant in UCP2 gene and body fat distribution, serum lipid profile in Chinese]. | 2000 | 4 |
About Junling Tang
Junling Tang is a scholar working on Endocrinology, Diabetes and Metabolism, Obstetrics and Gynecology, Cancer Research, Physiology and Cardiology and Cardiovascular Medicine, having authored 52 papers that have together received 1.0k indexed citations. Recurring topics across this work include Diabetes, Cardiovascular Risks, and Lipoproteins (16 papers), Diabetes Management and Research (9 papers), Metabolism, Diabetes, and Cancer (8 papers), Diabetes Treatment and Management (6 papers), Liver Disease Diagnosis and Treatment (5 papers), Gestational Diabetes Research and Management (4 papers), Cardiovascular Function and Risk Factors (3 papers) and MicroRNA in disease regulation (3 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (417 citations), Orthopedics and Sports Medicine (142 citations), Obstetrics and Gynecology (120 citations), Nephrology (45 citations) and Epidemiology (180 citations). Junling Tang has collaborated with scholars based in China, India and South Korea. Frequent co-authors include Weiping Jia, Yuqian Bao, Huijuan Lu, Xiaojing Ma, Xiaoping Pan, Mi Zhou, Xuhong Hou, Jiemin Pan, Jian Zhou and Kun‐san Xiang. Their work appears in journals such as Clinical and Experimental Pharmacology and Physiology, Diabetes Technology & Therapeutics, Acta Pharmacologica Sinica, PLoS ONE and Scientific Reports.
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.