Jun Liang
Impact in
- Aquatic Science top 2%
- Aquaculture Nutrition and Growth
- Aquatic life and conservation
- Nephrology top 5%
- Gout, Hyperuricemia, Uric Acid
Papers in
-
- Diet, Metabolism, and Disease 8
- Diabetes Treatment and Management 6
- Diabetes, Cardiovascular Risks, and Lipoproteins 6
- Co-authors
- Lu Qi (18 shared papers)Xuekui Liu (30 shared papers)Huazhong Shu (1 shared paper)Limin Luo (1 shared paper)Jean-Louis Coatrieux (1 shared paper)Hongqing Zhu (1 shared paper)Jichang Jian (4 shared papers)Lihua Chen (3 shared papers)
- Journals
- PLoS ONE (6 papers)Cell Biochemistry and Biophysics (4 papers)Frontiers in Endocrinology (4 papers)Journal of Clinical Hypertension (3 papers)Medicine (3 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Jun Liang
85 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 126
- Aquatic Science 183
- Nephrology 131
- Endocrinology, Diabetes and Metabolism 300
- Immunology 249
- Computer Vision and Pattern Recognition 149
Countries citing papers authored by Jun Liang
This map shows the geographic impact of Jun Liang'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 Liang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Liang more than expected).
Fields of papers citing papers by Jun Liang
This network shows the impact of papers produced by Jun Liang. 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 Liang. The network helps show where Jun Liang may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Liang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 88 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2006 | 159 | |
| 2 | 2018 | 156 | |
| 3 | 2018 | 62 | |
| 4 | 2013 | 61 | |
| 5 | 2019 | 60 | |
| 6 | 2010 | 41 | |
| 7 | 2012 | 37 | |
| 8 | 2012 | 35 | |
| 9 | 2009 | 33 | |
| 10 | 2009 | 33 | |
| 11 | 2019 | 33 | |
| 12 | 2017 | 32 | |
| 13 | 2012 | 31 | |
| 14 | 2021 | 30 | |
| 15 | 2012 | 27 | |
| 16 | 2009 | 27 | |
| 17 | 2014 | 25 | |
| 18 | 2007 | 25 | |
| 19 | 2013 | 23 | |
| 20 | 2014 | 23 |
About Jun Liang
Jun Liang is a scholar working on Molecular Biology, Endocrinology, Diabetes and Metabolism, Epidemiology, Surgery and Cardiology and Cardiovascular Medicine, having authored 88 papers that have together received 1.5k indexed citations. Recurring topics across this work include Liver Disease Diagnosis and Treatment (17 papers), Pancreatic function and diabetes (10 papers), Gout, Hyperuricemia, Uric Acid (8 papers), Diet, Metabolism, and Disease (8 papers), Diet and metabolism studies (7 papers), Adipokines, Inflammation, and Metabolic Diseases (6 papers), Diabetes Treatment and Management (6 papers) and Diabetes, Cardiovascular Risks, and Lipoproteins (6 papers). The work is most often cited by research in Aquatic Science (183 citations), Nephrology (131 citations), Endocrinology, Diabetes and Metabolism (300 citations), Immunology (249 citations) and Computer Vision and Pattern Recognition (149 citations). Jun Liang has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Lu Qi, Xuekui Liu, Huazhong Shu, Limin Luo, Jean-Louis Coatrieux, Hongqing Zhu, Jichang Jian, Lihua Chen, Huang Yu and Emmanuel Delwin Abarike. Their work appears in journals such as PLoS ONE, Cell Biochemistry and Biophysics, Frontiers in Endocrinology, Journal of Clinical Hypertension and Medicine.
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.