Jun Dai
Impact in
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- Circadian rhythm and melatonin
- Cell Biology top 1%
- Microtubule and mitosis dynamics
- Cellular transport and secretion
Papers in
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- Genomics and Chromatin Dynamics 6
- Ubiquitin and proteasome pathways 3
- Retinoids in leukemia and cellular processes 3
- DNA Repair Mechanisms 2
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- Circadian rhythm and melatonin 10
- Co-authors
- Jonathan M.G. Higgins (5 shared papers)Stephen S. Taylor (1 shared paper)Steven M. Hill (7 shared papers)Lin Yuan (5 shared papers)Beth A. Sullivan (1 shared paper)Gary J. Gorbsky (1 shared paper)John R. Daum (1 shared paper)Budhaditya Banerjee (1 shared paper)
- Journals
- Cancer Letters (3 papers)Journal of Cellular Physiology (3 papers)Developmental Cell (2 papers)International Journal of Molecular Sciences (2 papers)Journal of Pineal Research (2 papers)
- Partner nations
- United StatesChinaSwitzerland
In The Last Decade
Jun Dai
26 papers receiving 1.8k citations
Peers
Comparison fields: 5 of 98
- Endocrine and Autonomic Systems 392
- Cell Biology 792
- Molecular Biology 1.2k
- Aging 25
- Biological Psychiatry 20
Countries citing papers authored by Jun Dai
This map shows the geographic impact of Jun Dai'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 Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Dai more than expected).
Fields of papers citing papers by Jun Dai
This network shows the impact of papers produced by Jun Dai. 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 Dai. The network helps show where Jun Dai may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Dai, 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 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 377 | |
| 2 | 2005 | 289 | |
| 3 | 2006 | 180 | |
| 4 | 2002 | 126 | |
| 5 | 2002 | 120 | |
| 6 | 2007 | 95 | |
| 7 | 2004 | 93 | |
| 8 | 2002 | 66 | |
| 9 | 2005 | 53 | |
| 10 | 2014 | 53 | |
| 11 | 1998 | 50 | |
| 12 | 2000 | 42 | |
| 13 | 2009 | 41 | |
| 14 | 2017 | 36 | |
| 15 | 2018 | 31 | |
| 16 | 2001 | 29 | |
| 17 | 2013 | 29 | |
| 18 | 2017 | 21 | |
| 19 | 2005 | 21 | |
| 20 | 2010 | 21 |
About Jun Dai
Jun Dai is a scholar working on Molecular Biology, Endocrine and Autonomic Systems, Cell Biology, Genetics and Dermatology, having authored 26 papers that have together received 1.8k indexed citations. Recurring topics across this work include Circadian rhythm and melatonin (10 papers), Microtubule and mitosis dynamics (8 papers), Estrogen and related hormone effects (8 papers), Genomics and Chromatin Dynamics (6 papers), Ubiquitin and proteasome pathways (3 papers), Retinoids in leukemia and cellular processes (3 papers), Cellular transport and secretion (3 papers) and DNA Repair Mechanisms (2 papers). The work is most often cited by research in Endocrine and Autonomic Systems (392 citations), Cell Biology (792 citations), Molecular Biology (1.2k citations), Aging (25 citations) and Biological Psychiatry (20 citations). Jun Dai has collaborated with scholars based in United States, China and Switzerland. Frequent co-authors include Jonathan M.G. Higgins, Stephen S. Taylor, Steven M. Hill, Lin Yuan, Beth A. Sullivan, Gary J. Gorbsky, John R. Daum, Budhaditya Banerjee, P. Todd Stukenberg and Fangwei Wang. Their work appears in journals such as Cancer Letters, Journal of Cellular Physiology, Developmental Cell, International Journal of Molecular Sciences and Journal of Pineal Research.
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.