Can Tan
Impact in
- Geriatrics and Gerontology top 5%
- Sirtuins and Resveratrol in Medicine
-
- Genomics, phytochemicals, and oxidative stress
- Ubiquitin and proteasome pathways
- Glutathione Transferases and Polymorphisms
- Histone Deacetylase Inhibitors Research
Papers in
-
- Ubiquitin and proteasome pathways 4
- Histone Deacetylase Inhibitors Research 2
- Genetics 4
- Genomic variations and chromosomal abnormalities 2
- Craniofacial Disorders and Treatments 2
- Genetics and Neurodevelopmental Disorders 1
- Co-authors
- Beixue Gao (4 shared papers)Deyu Fang (4 shared papers)Tongde Wu (1 shared paper)Donna D. Zhang (1 shared paper)Pak Kin Wong (1 shared paper)Toshihiro Nakajima (1 shared paper)Fei Zhao (1 shared paper)Naoko Yagishita (1 shared paper)
- Journals
- Cell Discovery (1 paper)Life Science Alliance (1 paper)Blood (1 paper)Biochemical and Biophysical Research Communications (1 paper)Genes & Development (1 paper)
- Partner nations
- United StatesChinaJapan
In The Last Decade
Can Tan
19 papers receiving 737 citations
Peers
Comparison fields: 5 of 84
- Geriatrics and Gerontology 61
- Molecular Biology 475
- Cell Biology 98
- Physiology 24
- Cancer Research 65
Countries citing papers authored by Can Tan
This map shows the geographic impact of Can 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 Can Tan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Can Tan more than expected).
Fields of papers citing papers by Can Tan
This network shows the impact of papers produced by Can 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 Can Tan. The network helps show where Can Tan may publish in the future.
Co-authors
The 25 scholars most cited alongside Can 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 | 2014 | 307 | |
| 2 | 2013 | 163 | |
| 3 | 2015 | 68 | |
| 4 | 2018 | 50 | |
| 5 | 2022 | 48 | |
| 6 | 2023 | 20 | |
| 7 | 2010 | 18 | |
| 8 | 2010 | 13 | |
| 9 | 2023 | 9 | |
| 10 | 2015 | 8 | |
| 11 | 2021 | 8 | |
| 12 | 2024 | 7 | |
| 13 | 2024 | 6 | |
| 14 | 2011 | 6 | |
| 15 | 2023 | 3 | |
| 16 | 2023 | 3 | |
| 17 | 2023 | 3 | |
| 18 | 2014 | 3 | |
| 19 | 2023 | 1 | |
| 20 | 2025 | 0 |
About Can Tan
Can Tan is a scholar working on Molecular Biology, Genetics, Surgery, Genetics and Epidemiology, having authored 20 papers that have together received 744 indexed citations. Recurring topics across this work include Ubiquitin and proteasome pathways (4 papers), Ovarian function and disorders (2 papers), Genomic variations and chromosomal abnormalities (2 papers), Craniofacial Disorders and Treatments (2 papers), Histone Deacetylase Inhibitors Research (2 papers), Autophagy in Disease and Therapy (2 papers), Reproductive Biology and Fertility (2 papers) and Genetics and Neurodevelopmental Disorders (1 paper). The work is most often cited by research in Geriatrics and Gerontology (61 citations), Molecular Biology (475 citations), Cell Biology (98 citations), Physiology (24 citations) and Cancer Research (65 citations). Can Tan has collaborated with scholars based in United States, China and Japan. Frequent co-authors include Beixue Gao, Deyu Fang, Tongde Wu, Donna D. Zhang, Pak Kin Wong, Toshihiro Nakajima, Fei Zhao, Naoko Yagishita, Eli Chapman and Sinyi Kong. Their work appears in journals such as Cell Discovery, Life Science Alliance, Blood, Biochemical and Biophysical Research Communications and Genes & Development.
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.