Chee Eng Tan
Impact in
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- Diabetes, Cardiovascular Risks, and Lipoproteins
Papers in
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- Diabetes, Cardiovascular Risks, and Lipoproteins 6
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- Adipose Tissue and Metabolism 2
- Co-authors
- E Shyong Tai (16 shared papers)Suok Kai Chew (9 shared papers)José M. Ordovás (7 shared papers)Lip Ping Low (3 shared papers)Dolores Corella (4 shared papers)Jeffery Cutter (4 shared papers)Derrick Heng (3 shared papers)Mabel Deurenberg‐Yap (3 shared papers)
- Journals
- Journal of Lipid Research (2 papers)Diabetes Care (2 papers)Atherosclerosis (2 papers)Neurology (1 paper)Current Opinion in Lipidology (1 paper)
- Partner nations
- SingaporeUnited StatesSpain
In The Last Decade
Chee Eng Tan
25 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 88
- Endocrinology, Diabetes and Metabolism 383
- Cardiology and Cardiovascular Medicine 207
- Biochemistry 74
- Physiology 210
- Epidemiology 205
Countries citing papers authored by Chee Eng Tan
This map shows the geographic impact of Chee Eng Tan'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 Chee Eng Tan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chee Eng Tan more than expected).
Fields of papers citing papers by Chee Eng Tan
This network shows the impact of papers produced by Chee Eng Tan. 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 Chee Eng Tan. The network helps show where Chee Eng Tan may publish in the future.
Co-authors
The 25 scholars most cited alongside Chee Eng Tan, 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 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Metabolic syndrome: recent prevalence in East and Southeast Asian populations. | 2007 | 187 |
| 2 | 2014 | 128 | |
| 3 | 2003 | 122 | |
| 4 | 2005 | 120 | |
| 5 | 2004 | 100 | |
| 6 | 2003 | 86 | |
| 7 | 2008 | 79 | |
| 8 | 2004 | 73 | |
| 9 | 2004 | 72 | |
| 10 | 2006 | 61 | |
| 11 | 2005 | 54 | |
| 12 | 2003 | 54 | |
| 13 | 2018 | 36 | |
| 14 | 2006 | 33 | |
| 15 | 2004 | 31 | |
| 16 | 2017 | 28 | |
| 17 | 2003 | 27 | |
| 18 | 2004 | 26 | |
| 19 | 2003 | 20 | |
| 20 | 2001 | 15 |
About Chee Eng Tan
Chee Eng Tan is a scholar working on Endocrinology, Diabetes and Metabolism, Physiology, Surgery, Molecular Biology and Epidemiology, having authored 25 papers that have together received 1.4k indexed citations. Recurring topics across this work include Diabetes, Cardiovascular Risks, and Lipoproteins (6 papers), Lipoproteins and Cardiovascular Health (4 papers), Obesity, Physical Activity, Diet (2 papers), Liver Disease Diagnosis and Treatment (2 papers), Lipid metabolism and biosynthesis (2 papers), Nutritional Studies and Diet (2 papers), Adipose Tissue and Metabolism (2 papers) and Peroxisome Proliferator-Activated Receptors (2 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (383 citations), Cardiology and Cardiovascular Medicine (207 citations), Biochemistry (74 citations), Physiology (210 citations) and Epidemiology (205 citations). Chee Eng Tan has collaborated with scholars based in Singapore, United States and Spain. Frequent co-authors include E Shyong Tai, Suok Kai Chew, José M. Ordovás, Lip Ping Low, Dolores Corella, Jeffery Cutter, Derrick Heng, Mabel Deurenberg‐Yap, Kee Seng Chia and Xian Adiconis. Their work appears in journals such as Journal of Lipid Research, Diabetes Care, Atherosclerosis, Neurology and Current Opinion in Lipidology.
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.