Kun Wen

1.9k citations
37 papers · 1.3k · h-index 17

Impact in

Papers in

Kun Wen

37 papers receiving 1.2k citations

Peers

Kun Wen
Comparison fields: 5 of 96
  • Infectious Diseases 886
  • Animal Science and Zoology 86
  • Neurology 121
  • Public Health, Environmental and Occupational Health 213
  • Modeling and Simulation 33
Replace Francesca Colavita with:
Francesca Colavita Italy
Masafumi Sakata Japan
Hiroshi Katoh Japan
Kao‐Jean Huang Taiwan
Jianying Liu China
Amrita Ojha United States
Rüdiger Groß Germany
Changfa Fan China
Ikuyo Takayama Japan
Kun Wen relative to Francesca Colavita Italy Francesca Colavita's profile →
Citations per field
00.5×1.5×2.3×
Francesca Colavita · 1×
Citations per year

Countries citing papers authored by Kun Wen

Since Specialization
Citations

This map shows the geographic impact of Kun Wen'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 Wen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kun Wen more than expected).

Fields of papers citing papers by Kun Wen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kun Wen. 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 Wen. The network helps show where Kun Wen may publish in the future.

Co-authors

The 25 scholars most cited alongside Kun Wen, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Kun Wen Line = papers co-authored together Kun Wen links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006297
2 2020146
3 2005123
4 200498
5 202076
6 201161
7 202047
8 200539
9 201138
10 201135
11 201330
12 200829
13 201628
14 202126
15 202024
16 201124
17 201816
18 201614
19 202313
20 202212

About Kun Wen

Kun Wen is a scholar working on Infectious Diseases, Public Health, Environmental and Occupational Health, Immunology, Molecular Biology and Radiology, Nuclear Medicine and Imaging, having authored 37 papers that have together received 1.3k indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (13 papers), Mosquito-borne diseases and control (7 papers), Viral Infections and Vectors (6 papers), COVID-19 Clinical Research Studies (5 papers), SARS-CoV-2 detection and testing (4 papers), Immune Cell Function and Interaction (4 papers), Malaria Research and Control (4 papers) and Monoclonal and Polyclonal Antibodies Research (4 papers). The work is most often cited by research in Infectious Diseases (886 citations), Animal Science and Zoology (86 citations), Neurology (121 citations), Public Health, Environmental and Occupational Health (213 citations) and Modeling and Simulation (33 citations). Kun Wen has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Chi‐Ming Che, Yuxian Pan, Liwen Qiu, Kwok‐Yung Yuen, Wei Hao, Vincent Chi‐Chung Cheng, Hongwei Zhou, Yanqing Ding, Yadi Wang and Dongmei Hu. Their work appears in journals such as Clinical and Vaccine Immunology, Frontiers in Immunology, Food Bioscience, Protein & Cell and Clinical Microbiology and Infection.

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.

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