Kun Yan
Impact in
- Earth-Surface Processes top 10%
- Coastal and Marine Dynamics
- Atmospheric Science top 10%
- Tropical and Extratropical Cyclones Research
Papers in
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- Neuroscience and Neuropharmacology Research 2
-
- Cellular transport and secretion 2
- Co-authors
- Maialen Irazoqui Apecechea (1 shared paper)Martin Verlaan (2 shared papers)Joao de Lima Rego (1 shared paper)Sanne Muis (1 shared paper)Job Dullaart (1 shared paper)Kristine S. Madsen (1 shared paper)Jian Su (1 shared paper)Mark M. Rasenick (3 shared papers)
- Journals
- Muscle & Nerve (2 papers)Journal of Neurochemistry (2 papers)Scientific Reports (1 paper)International Journal of Advancements in Computing Technology (1 paper)Journal of Computer Assisted Tomography (1 paper)
- Partner nations
- United StatesNetherlandsChina
In The Last Decade
Kun Yan
10 papers receiving 301 citations
Peers
Comparison fields: 5 of 87
- Earth-Surface Processes 62
- Atmospheric Science 129
- Oceanography 83
- Global and Planetary Change 102
- Cell Biology 42
Countries citing papers authored by Kun Yan
This map shows the geographic impact of Kun Yan'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 Yan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kun Yan more than expected).
Fields of papers citing papers by Kun Yan
This network shows the impact of papers produced by Kun Yan. 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 Yan. The network helps show where Kun Yan may publish in the future.
Co-authors
The 25 scholars most cited alongside Kun Yan, 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 | 2020 | 180 | |
| 2 | 1996 | 33 | |
| 3 | 2001 | 24 | |
| 4 | Specific associations between tubulin and G proteins: participation of cytoskeletal elements in cellular signal transduction. | 1990 | 19 |
| 5 | 1997 | 17 | |
| 6 | 2017 | 16 | |
| 7 | 1998 | 9 | |
| 8 | 1998 | 4 | |
| 9 | Global-to-local scale storm surge modelling on tropical cyclone affected coasts | 2017 | 3 |
| 10 | 2012 | 1 | |
| 11 | 2025 | 0 | |
| 12 | 2013 | 0 |
About Kun Yan
Kun Yan is a scholar working on Cellular and Molecular Neuroscience, Cell Biology, Molecular Biology, Oceanography and Atmospheric Science, having authored 12 papers that have together received 306 indexed citations. Recurring topics across this work include Tropical and Extratropical Cyclones Research (2 papers), Protein Kinase Regulation and GTPase Signaling (2 papers), Neuroscience and Neuropharmacology Research (2 papers), Cellular transport and secretion (2 papers), Energy Efficient Wireless Sensor Networks (1 paper), Medical Imaging Techniques and Applications (1 paper), IoT-based Smart Home Systems (1 paper) and Neural Networks and Applications (1 paper). The work is most often cited by research in Earth-Surface Processes (62 citations), Atmospheric Science (129 citations), Oceanography (83 citations), Global and Planetary Change (102 citations) and Cell Biology (42 citations). Kun Yan has collaborated with scholars based in United States, Netherlands and China. Frequent co-authors include Maialen Irazoqui Apecechea, Martin Verlaan, Joao de Lima Rego, Sanne Muis, Job Dullaart, Kristine S. Madsen, Jian Su, Mark M. Rasenick, Nan Wang and J. Popova. Their work appears in journals such as Muscle & Nerve, Journal of Neurochemistry, Scientific Reports, International Journal of Advancements in Computing Technology and Journal of Computer Assisted Tomography.
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.