Kun Tan
Impact in
- Reproductive Medicine top 2%
- Sperm and Testicular Function
- Aging top 10%
Papers in
-
- Pluripotent Stem Cells Research 6
- Renal and related cancers 5
- RNA Research and Splicing 5
- Epigenetics and DNA Methylation 5
- RNA and protein synthesis mechanisms 4
-
- Reproductive Biology and Fertility 8
- Co-authors
- Miles Wilkinson (17 shared papers)Jianhui Tian (13 shared papers)Lei An (12 shared papers)Kai Miao (11 shared papers)Dwayne G. Stupack (1 shared paper)Abhishek Sohni (3 shared papers)Dana Burow (3 shared papers)Dirk G. de Rooij (2 shared papers)
- Journals
- Proceedings of the National Academy of Sciences (4 papers)Nucleic Acids Research (3 papers)Development (2 papers)Cell Reports (2 papers)Biology of Reproduction (2 papers)
- Partner nations
- ChinaUnited StatesIndonesia
In The Last Decade
Kun Tan
43 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 86
- Reproductive Medicine 300
- Aging 23
- Public Health, Environmental and Occupational Health 297
- Molecular Biology 651
- Cancer Research 121
Countries citing papers authored by Kun Tan
This map shows the geographic impact of Kun 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 Kun Tan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kun Tan more than expected).
Fields of papers citing papers by Kun Tan
This network shows the impact of papers produced by Kun 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 Kun Tan. The network helps show where Kun Tan may publish in the future.
Co-authors
The 25 scholars most cited alongside Kun 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 43 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 229 | |
| 2 | 2020 | 85 | |
| 3 | 2022 | 82 | |
| 4 | 2020 | 65 | |
| 5 | 2020 | 56 | |
| 6 | 2016 | 54 | |
| 7 | 2020 | 43 | |
| 8 | 2013 | 41 | |
| 9 | 2022 | 40 | |
| 10 | 2017 | 40 | |
| 11 | 2016 | 40 | |
| 12 | 2015 | 36 | |
| 13 | 2016 | 32 | |
| 14 | 2013 | 28 | |
| 15 | 2016 | 28 | |
| 16 | 2014 | 27 | |
| 17 | 2019 | 27 | |
| 18 | 2020 | 27 | |
| 19 | 2015 | 25 | |
| 20 | 2018 | 25 |
About Kun Tan
Kun Tan is a scholar working on Molecular Biology, Public Health, Environmental and Occupational Health, Genetics, Pediatrics, Perinatology and Child Health and Reproductive Medicine, having authored 43 papers that have together received 1.3k indexed citations. Recurring topics across this work include Reproductive Biology and Fertility (8 papers), Pluripotent Stem Cells Research (6 papers), Renal and related cancers (5 papers), RNA Research and Splicing (5 papers), Epigenetics and DNA Methylation (5 papers), Sperm and Testicular Function (5 papers), Genetic and Clinical Aspects of Sex Determination and Chromosomal Abnormalities (4 papers) and RNA and protein synthesis mechanisms (4 papers). The work is most often cited by research in Reproductive Medicine (300 citations), Aging (23 citations), Public Health, Environmental and Occupational Health (297 citations), Molecular Biology (651 citations) and Cancer Research (121 citations). Kun Tan has collaborated with scholars based in China, United States and Indonesia. Frequent co-authors include Miles Wilkinson, Jianhui Tian, Lei An, Kai Miao, Dwayne G. Stupack, Abhishek Sohni, Dana Burow, Dirk G. de Rooij, Saher Sue Hammoud and Hye-Won Song. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research, Development, Cell Reports and Biology of Reproduction.
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.