Kun Xu
Impact in
- Molecular Biology top 10%
- CRISPR and Genetic Engineering
- Fungal and yeast genetics research
- Muscle Physiology and Disorders
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- Computational Drug Discovery Methods
Papers in
-
- CRISPR and Genetic Engineering 24
- Fungal and yeast genetics research 5
- Muscle Physiology and Disorders 4
- RNA Interference and Gene Delivery 2
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- Aquaculture disease management and microbiota 3
- Co-authors
- Zhiying Zhang (33 shared papers)Yuan‐Ping Pang (4 shared papers)Emanuele Perola (4 shared papers)Chonghua Ren (12 shared papers)Franklyn G. Prendergast (3 shared papers)Tingting Zhang (5 shared papers)Zhongtian Liu (8 shared papers)Rui Wang (1 shared paper)
- Journals
- Fish & Shellfish Immunology (3 papers)Analytical Biochemistry (3 papers)Vaccine (2 papers)FEBS Letters (2 papers)PLoS ONE (2 papers)
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Kun Xu
62 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 95
- Molecular Biology 658
- Computational Theory and Mathematics 167
- Biological Psychiatry 8
- Immunology 75
- Pharmaceutical Science 20
Countries citing papers authored by Kun Xu
This map shows the geographic impact of Kun Xu'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 Xu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kun Xu more than expected).
Fields of papers citing papers by Kun Xu
This network shows the impact of papers produced by Kun Xu. 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 Xu. The network helps show where Kun Xu may publish in the future.
Co-authors
The 25 scholars most cited alongside Kun Xu, 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 67 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 141 | |
| 2 | 2023 | 114 | |
| 3 | 2000 | 108 | |
| 4 | 2001 | 85 | |
| 5 | 2017 | 66 | |
| 6 | 2014 | 65 | |
| 7 | 2023 | 44 | |
| 8 | 2017 | 40 | |
| 9 | 2018 | 40 | |
| 10 | 2015 | 36 | |
| 11 | 2013 | 34 | |
| 12 | 2024 | 34 | |
| 13 | 2001 | 32 | |
| 14 | 2018 | 31 | |
| 15 | 2016 | 28 | |
| 16 | 2015 | 27 | |
| 17 | 2011 | 26 | |
| 18 | 2016 | 25 | |
| 19 | 2012 | 24 | |
| 20 | 2013 | 23 |
About Kun Xu
Kun Xu is a scholar working on Molecular Biology, Immunology, Genetics, Animal Science and Zoology and Computational Theory and Mathematics, having authored 67 papers that have together received 1.4k indexed citations. Recurring topics across this work include CRISPR and Genetic Engineering (24 papers), Fungal and yeast genetics research (5 papers), Muscle Physiology and Disorders (4 papers), Aquaculture disease management and microbiota (3 papers), Computational Drug Discovery Methods (3 papers), Virus-based gene therapy research (2 papers), RNA Interference and Gene Delivery (2 papers) and Animal Genetics and Reproduction (2 papers). The work is most often cited by research in Molecular Biology (658 citations), Computational Theory and Mathematics (167 citations), Biological Psychiatry (8 citations), Immunology (75 citations) and Pharmaceutical Science (20 citations). Kun Xu has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Zhiying Zhang, Yuan‐Ping Pang, Emanuele Perola, Chonghua Ren, Franklyn G. Prendergast, Tingting Zhang, Zhongtian Liu, Rui Wang, Thomas M. Kollmeyer and Kaiyong Cai. Their work appears in journals such as Fish & Shellfish Immunology, Analytical Biochemistry, Vaccine, FEBS Letters and PLoS ONE.
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.