Ken Wei Tan
Impact in
-
- Chronic Kidney Disease and Diabetes
- Modeling and Simulation top 10%
- COVID-19 epidemiological studies
Papers in
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- Mosquito-borne diseases and control 6
- Zoonotic diseases and public health 1
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- COVID-19 epidemiological studies 4
- Co-authors
- Borame Sue Lee Dickens (14 shared papers)Kee Seng Chia (2 shared papers)Daniel P. K. Ng (1 shared paper)David Koh (1 shared paper)Bee Choo Tai (1 shared paper)Alex R. Cook (13 shared papers)Joel Ruihan Koo (10 shared papers)Jue Tao Lim (10 shared papers)
- Journals
- Viruses (3 papers)PLoS Computational Biology (2 papers)Scientific Reports (1 paper)Metabolism (1 paper)International Journal of Environmental Research and Public Health (1 paper)
- Partner nations
- SingaporeNew ZealandUnited States
In The Last Decade
Ken Wei Tan
19 papers receiving 397 citations
Peers
Comparison fields: 5 of 88
- Nephrology 31
- Modeling and Simulation 19
- Endocrinology, Diabetes and Metabolism 61
- Cardiology and Cardiovascular Medicine 66
- Insect Science 37
Countries citing papers authored by Ken Wei Tan
This map shows the geographic impact of Ken Wei 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 Ken Wei Tan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ken Wei Tan more than expected).
Fields of papers citing papers by Ken Wei Tan
This network shows the impact of papers produced by Ken Wei 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 Ken Wei Tan. The network helps show where Ken Wei Tan may publish in the future.
Co-authors
The 25 scholars most cited alongside Ken Wei 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
| # | Work | ||
|---|---|---|---|
| 1 | 2005 | 121 | |
| 2 | 2017 | 43 | |
| 3 | 2021 | 35 | |
| 4 | 2020 | 24 | |
| 5 | 2019 | 23 | |
| 6 | 2021 | 23 | |
| 7 | 2020 | 20 | |
| 8 | 2020 | 20 | |
| 9 | 2020 | 19 | |
| 10 | 2022 | 16 | |
| 11 | 1984 | 10 | |
| 12 | 2022 | 9 | |
| 13 | 2021 | 9 | |
| 14 | 2021 | 8 | |
| 15 | 2019 | 8 | |
| 16 | 2022 | 7 | |
| 17 | 2016 | 6 | |
| 18 | 2022 | 4 | |
| 19 | 2022 | 3 | |
| 20 | 2021 | 0 |
About Ken Wei Tan
Ken Wei Tan is a scholar working on Public Health, Environmental and Occupational Health, Modeling and Simulation, Cardiology and Cardiovascular Medicine, Epidemiology and Insect Science, having authored 20 papers that have together received 408 indexed citations. Recurring topics across this work include Mosquito-borne diseases and control (6 papers), COVID-19 epidemiological studies (4 papers), Insect symbiosis and bacterial influences (2 papers), Advanced Proteomics Techniques and Applications (1 paper), Sodium Intake and Health (1 paper), Zoonotic diseases and public health (1 paper), Diabetes and associated disorders (1 paper) and T-cell and B-cell Immunology (1 paper). The work is most often cited by research in Nephrology (31 citations), Modeling and Simulation (19 citations), Endocrinology, Diabetes and Metabolism (61 citations), Cardiology and Cardiovascular Medicine (66 citations) and Insect Science (37 citations). Ken Wei Tan has collaborated with scholars based in Singapore, New Zealand and United States. Frequent co-authors include Borame Sue Lee Dickens, Kee Seng Chia, Daniel P. K. Ng, David Koh, Bee Choo Tai, Alex R. Cook, Joel Ruihan Koo, Jue Tao Lim, Jamie A. Macpherson and Argyris Politis. Their work appears in journals such as Viruses, PLoS Computational Biology, Scientific Reports, Metabolism and International Journal of Environmental Research and Public Health.
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.