Semon Wu
Impact in
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- Diabetes, Cardiovascular Risks, and Lipoproteins
- Biological Psychiatry top 10%
Papers in
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- Epigenetics and DNA Methylation 4
- Epidemiology 16
- Adipokines, Inflammation, and Metabolic Diseases 13
- Co-authors
- Yu‐Lin Ko (58 shared papers)Lung‐An Hsu (49 shared papers)Ming‐Sheng Teng (49 shared papers)Hsin‐Hua Chou (27 shared papers)Yuchen Sun (6 shared papers)Leay‐Kiaw Er (9 shared papers)Chi‐Jen Chang (8 shared papers)Jeng-Feng Lin (13 shared papers)
- Journals
- International Journal of Molecular Sciences (7 papers)Atherosclerosis (6 papers)Genes (5 papers)PLoS ONE (4 papers)Metabolism (3 papers)
- Partner nations
- TaiwanUnited States
In The Last Decade
Semon Wu
70 papers receiving 1.4k citations
Semon Wu's Hit Papers
Peers
Comparison fields: 5 of 100
- Endocrinology, Diabetes and Metabolism 289
- Biological Psychiatry 40
- Cardiology and Cardiovascular Medicine 186
- Epidemiology 259
- Nephrology 50
Countries citing papers authored by Semon Wu
This map shows the geographic impact of Semon Wu'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 Semon Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Semon Wu more than expected).
Fields of papers citing papers by Semon Wu
This network shows the impact of papers produced by Semon Wu. 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 Semon Wu. The network helps show where Semon Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Semon Wu, 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 71 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Triglyceride Glucose-Body Mass Index Is a Simple and Clinically Useful Surrogate Marker for Insulin Resistance in Nondiabetic Individuals Hit paper breakdown → | 2016 | 425 |
| 2 | 2005 | 65 | |
| 3 | 2003 | 52 | |
| 4 | 2013 | 45 | |
| 5 | 2008 | 39 | |
| 6 | 2004 | 37 | |
| 7 | 2009 | 35 | |
| 8 | 2017 | 34 | |
| 9 | 2014 | 32 | |
| 10 | 2008 | 27 | |
| 11 | 2015 | 27 | |
| 12 | 2013 | 26 | |
| 13 | 2014 | 25 | |
| 14 | 2009 | 24 | |
| 15 | 2018 | 23 | |
| 16 | 2009 | 23 | |
| 17 | 2005 | 21 | |
| 18 | 2016 | 21 | |
| 19 | 2019 | 19 | |
| 20 | 2011 | 19 |
About Semon Wu
Semon Wu is a scholar working on Molecular Biology, Epidemiology, Surgery, Genetics and Immunology, having authored 71 papers that have together received 1.4k indexed citations. Recurring topics across this work include Adipokines, Inflammation, and Metabolic Diseases (13 papers), Genetic Associations and Epidemiology (7 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (6 papers), Lipoproteins and Cardiovascular Health (5 papers), IL-33, ST2, and ILC Pathways (4 papers), Epigenetics and DNA Methylation (4 papers), GDF15 and Related Biomarkers (4 papers) and Cholesterol and Lipid Metabolism (3 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (289 citations), Biological Psychiatry (40 citations), Cardiology and Cardiovascular Medicine (186 citations), Epidemiology (259 citations) and Nephrology (50 citations). Semon Wu has collaborated with scholars based in Taiwan and United States. Frequent co-authors include Yu‐Lin Ko, Lung‐An Hsu, Ming‐Sheng Teng, Hsin‐Hua Chou, Yuchen Sun, Leay‐Kiaw Er, Chi‐Jen Chang, Jeng-Feng Lin, Ying‐Shiung Lee and Mao‐Liang Chen. Their work appears in journals such as International Journal of Molecular Sciences, Atherosclerosis, Genes, PLoS ONE 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.