Kai‐Yun Chen
Impact in
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- Neurobiology and Insect Physiology Research
- Neuroscience and Neuropharmacology Research
- Aging top 5%
Papers in
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- Neurobiology and Insect Physiology Research 9
- Co-authors
- David E. Featherstone (14 shared papers)Yung‐Hsiao Chiang (37 shared papers)Qi Sheng (3 shared papers)Hanning Wang (16 shared papers)Guoan Xiang (15 shared papers)Rami Ahmad Shahror (6 shared papers)Chaur‐Jong Hu (5 shared papers)Jing-Huei Lai (10 shared papers)
- Journals
- International Journal of Molecular Sciences (9 papers)PLoS ONE (4 papers)Journal of Neurotrauma (4 papers)Journal of Visualized Experiments (4 papers)Journal of Neuroscience (3 papers)
- Partner nations
- TaiwanChinaUnited States
In The Last Decade
Kai‐Yun Chen
120 papers receiving 2.8k citations
Peers
Comparison fields: 5 of 137
- Cellular and Molecular Neuroscience 643
- Aging 52
- Neurology 351
- Neurology 193
- Developmental Neuroscience 93
Countries citing papers authored by Kai‐Yun Chen
This map shows the geographic impact of Kai‐Yun Chen'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 Kai‐Yun Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kai‐Yun Chen more than expected).
Fields of papers citing papers by Kai‐Yun Chen
This network shows the impact of papers produced by Kai‐Yun Chen. 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 Kai‐Yun Chen. The network helps show where Kai‐Yun Chen may publish in the future.
Co-authors
The 25 scholars most cited alongside Kai‐Yun Chen, 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 123 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2006 | 142 | |
| 2 | 2005 | 140 | |
| 3 | 2020 | 130 | |
| 4 | 2009 | 107 | |
| 5 | 2007 | 103 | |
| 6 | 2020 | 102 | |
| 7 | 2017 | 97 | |
| 8 | 2011 | 81 | |
| 9 | 2020 | 74 | |
| 10 | 2005 | 73 | |
| 11 | 2011 | 65 | |
| 12 | 2017 | 63 | |
| 13 | 2019 | 59 | |
| 14 | 2002 | 55 | |
| 15 | 2014 | 54 | |
| 16 | 2009 | 49 | |
| 17 | 2013 | 46 | |
| 18 | 2018 | 44 | |
| 19 | 2022 | 40 | |
| 20 | 2021 | 39 |
About Kai‐Yun Chen
Kai‐Yun Chen is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Epidemiology, Neurology and Surgery, having authored 123 papers that have together received 2.8k indexed citations. Recurring topics across this work include Traumatic Brain Injury Research (11 papers), Neurobiology and Insect Physiology Research (9 papers), Mesenchymal stem cell research (7 papers), Parkinson's Disease Mechanisms and Treatments (7 papers), Traumatic Brain Injury and Neurovascular Disturbances (6 papers), Cellular transport and secretion (5 papers), Autism Spectrum Disorder Research (5 papers) and MicroRNA in disease regulation (5 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (643 citations), Aging (52 citations), Neurology (351 citations), Neurology (193 citations) and Developmental Neuroscience (93 citations). Kai‐Yun Chen has collaborated with scholars based in Taiwan, China and United States. Frequent co-authors include David E. Featherstone, Yung‐Hsiao Chiang, Qi Sheng, Hanning Wang, Guoan Xiang, Rami Ahmad Shahror, Chaur‐Jong Hu, Jing-Huei Lai, Richard W. Daniels and Catherine A. Collins. Their work appears in journals such as International Journal of Molecular Sciences, PLoS ONE, Journal of Neurotrauma, Journal of Visualized Experiments and Journal of Neuroscience.
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.