Jun Tan
Impact in
- Biological Psychiatry top 0.5%
- Tryptophan and brain disorders
- Neurology top 0.5%
- Neuroinflammation and Neurodegeneration Mechanisms
Papers in
- Neurology 25
- Neuroinflammation and Neurodegeneration Mechanisms 25
- Physiology 37
- Alzheimer's disease research and treatments 36
- Co-authors
- Terrence Town (18 shared papers)Brian Giunta (20 shared papers)Huayan Hou (14 shared papers)Kavon P. Rezai-Zadeh (7 shared papers)Jared C. Ehrhart (9 shared papers)R. Douglas Shytle (10 shared papers)Jin Zeng (7 shared papers)Takashi Mori (6 shared papers)
- Journals
- Journal of Biological Chemistry (4 papers)Molecular Psychiatry (2 papers)Alzheimer s & Dementia (2 papers)Current Alzheimer Research (2 papers)Neurobiology of Aging (2 papers)
- Partner nations
- United StatesChinaJapan
In The Last Decade
Jun Tan
61 papers receiving 5.9k citations
Peers
Comparison fields: 5 of 136
- Biological Psychiatry 694
- Neurology 1.7k
- Physiology 2.6k
- Developmental Neuroscience 275
- Complementary and alternative medicine 424
Countries citing papers authored by Jun Tan
This map shows the geographic impact of Jun 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 Jun Tan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Tan more than expected).
Fields of papers citing papers by Jun Tan
This network shows the impact of papers produced by Jun 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 Jun Tan. The network helps show where Jun Tan may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun 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 63 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2005 | 599 | |
| 2 | 2004 | 494 | |
| 3 | 2008 | 406 | |
| 4 | 2005 | 395 | |
| 5 | 2008 | 379 | |
| 6 | 2013 | 238 | |
| 7 | 2015 | 221 | |
| 8 | 2017 | 190 | |
| 9 | 2002 | 189 | |
| 10 | 2006 | 183 | |
| 11 | 2011 | 170 | |
| 12 | 2012 | 156 | |
| 13 | 2010 | 138 | |
| 14 | 2007 | 132 | |
| 15 | 2010 | 122 | |
| 16 | 2012 | 115 | |
| 17 | 2013 | 107 | |
| 18 | 2002 | 105 | |
| 19 | 2012 | 101 | |
| 20 | 2011 | 95 |
About Jun Tan
Jun Tan is a scholar working on Neurology, Physiology, Biological Psychiatry, Pharmacology and Psychiatry and Mental health, having authored 63 papers that have together received 6.1k indexed citations. Recurring topics across this work include Alzheimer's disease research and treatments (36 papers), Neuroinflammation and Neurodegeneration Mechanisms (25 papers), Tryptophan and brain disorders (9 papers), Cholinesterase and Neurodegenerative Diseases (7 papers), Dementia and Cognitive Impairment Research (5 papers), Immune cells in cancer (4 papers), Autism Spectrum Disorder Research (4 papers) and GDF15 and Related Biomarkers (3 papers). The work is most often cited by research in Biological Psychiatry (694 citations), Neurology (1.7k citations), Physiology (2.6k citations), Developmental Neuroscience (275 citations) and Complementary and alternative medicine (424 citations). Jun Tan has collaborated with scholars based in United States, China and Japan. Frequent co-authors include Terrence Town, Brian Giunta, Huayan Hou, Kavon P. Rezai-Zadeh, Jared C. Ehrhart, R. Douglas Shytle, Jin Zeng, Takashi Mori, Demian F. Obregon and Nan Sun. Their work appears in journals such as Journal of Biological Chemistry, Molecular Psychiatry, Alzheimer s & Dementia, Current Alzheimer Research and Neurobiology of Aging.
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.