Kun Yan
Impact in
- Earth-Surface Processes top 10%
- Coastal and Marine Dynamics
- Atmospheric Science top 10%
- Tropical and Extratropical Cyclones Research
Papers in
-
- Cellular transport and secretion 2
-
- Tuberculosis Research and Epidemiology 3
- Co-authors
- Martin Verlaan (2 shared papers)Sanne Muis (1 shared paper)Maialen Irazoqui Apecechea (1 shared paper)Job Dullaart (1 shared paper)Jian Su (1 shared paper)Joao de Lima Rego (1 shared paper)Kristine S. Madsen (1 shared paper)Mark M. Rasenick (3 shared papers)
- Journals
- Journal of Neurochemistry (2 papers)Muscle & Nerve (2 papers)PM&R (1 paper)International Journal of Infectious Diseases (1 paper)Frontiers in Marine Science (1 paper)
- Partner nations
- ChinaUnited StatesNetherlands
In The Last Decade
Kun Yan
15 papers receiving 485 citations
Peers
Comparison fields: 5 of 99
- Earth-Surface Processes 65
- Atmospheric Science 138
- Oceanography 79
- Global and Planetary Change 104
- Infectious Diseases 53
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 | 201 | |
| 2 | 2020 | 84 | |
| 3 | 1996 | 34 | |
| 4 | 2021 | 26 | |
| 5 | 2001 | 24 | |
| 6 | 1997 | 21 | |
| 7 | 2025 | 20 | |
| 8 | Specific associations between tubulin and G proteins: participation of cytoskeletal elements in cellular signal transduction. | 1990 | 19 |
| 9 | 2017 | 18 | |
| 10 | 2020 | 15 | |
| 11 | 1998 | 11 | |
| 12 | 2023 | 9 | |
| 13 | 1998 | 6 | |
| 14 | Global-to-local scale storm surge modelling on tropical cyclone affected coasts | 2017 | 3 |
| 15 | 2012 | 1 | |
| 16 | 2025 | 0 | |
| 17 | 2025 | 0 | |
| 18 | 2013 | 0 |
About Kun Yan
Kun Yan is a scholar working on Cell Biology, Infectious Diseases, Cellular and Molecular Neuroscience, Oceanography and Surgery, having authored 18 papers that have together received 492 indexed citations. Recurring topics across this work include Tuberculosis Research and Epidemiology (3 papers), Diagnosis and treatment of tuberculosis (3 papers), Tropical and Extratropical Cyclones Research (2 papers), Protein Kinase Regulation and GTPase Signaling (2 papers), Neuroscience and Neuropharmacology Research (2 papers), Infectious Diseases and Tuberculosis (2 papers), Cellular transport and secretion (2 papers) and Occupational Health and Safety Research (1 paper). The work is most often cited by research in Earth-Surface Processes (65 citations), Atmospheric Science (138 citations), Oceanography (79 citations), Global and Planetary Change (104 citations) and Infectious Diseases (53 citations). Kun Yan has collaborated with scholars based in China, United States and Netherlands. Frequent co-authors include Martin Verlaan, Sanne Muis, Maialen Irazoqui Apecechea, Job Dullaart, Jian Su, Joao de Lima Rego, Kristine S. Madsen, Mark M. Rasenick, Bhagwan T. Shahani and Nan Wang. Their work appears in journals such as Journal of Neurochemistry, Muscle & Nerve, PM&R, International Journal of Infectious Diseases and Frontiers in Marine Science.
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.