Jun Lan
Impact in
- Infectious Diseases top 0.2%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
- SARS-CoV-2 detection and testing
- Viral gastroenteritis research and epidemiology
- Animal Science and Zoology top 1%
- Animal Virus Infections Studies
Papers in
-
- SARS-CoV-2 and COVID-19 Research 16
- COVID-19 Clinical Research Studies 9
- Viral gastroenteritis research and epidemiology 3
-
- Animal Virus Infections Studies 7
- Co-authors
- Xinquan Wang (16 shared papers)Linqi Zhang (6 shared papers)Shilong Fan (8 shared papers)Jinfang Yu (3 shared papers)Sisi Shan (3 shared papers)Jiwan Ge (3 shared papers)Xuanling Shi (3 shared papers)Qi Zhang (3 shared papers)
- Journals
- Nature Communications (3 papers)Structure (3 papers)mBio (2 papers)Frontiers in Immunology (2 papers)PLoS Pathogens (2 papers)
- Partner nations
- ChinaUnited StatesSouth Korea
In The Last Decade
Jun Lan
32 papers receiving 4.8k citations
Jun Lan's Hit Papers
Peers
Comparison fields: 5 of 132
- Infectious Diseases 3.6k
- Animal Science and Zoology 469
- Computational Theory and Mathematics 666
- Neurology 343
- Modeling and Simulation 96
Countries citing papers authored by Jun Lan
This map shows the geographic impact of Jun Lan'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 Jun Lan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Lan more than expected).
Fields of papers citing papers by Jun Lan
This network shows the impact of papers produced by Jun Lan. 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 Jun Lan. The network helps show where Jun Lan may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Lan, 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 36 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Structure of the SARS-CoV-2 spike receptor-binding domain bound to the ACE2 receptor Hit paper breakdown → | 2020 | 4132 |
| 2 | 2021 | 138 | |
| 3 | 2019 | 107 | |
| 4 | 2021 | 75 | |
| 5 | 1998 | 67 | |
| 6 | 2021 | 48 | |
| 7 | 2018 | 42 | |
| 8 | 2022 | 30 | |
| 9 | 2020 | 29 | |
| 10 | 2021 | 28 | |
| 11 | 2022 | 25 | |
| 12 | 2018 | 25 | |
| 13 | 2021 | 24 | |
| 14 | 2022 | 21 | |
| 15 | 2021 | 19 | |
| 16 | 2015 | 12 | |
| 17 | 2023 | 11 | |
| 18 | 2021 | 11 | |
| 19 | 2016 | 11 | |
| 20 | 2022 | 10 |
About Jun Lan
Jun Lan is a scholar working on Infectious Diseases, Animal Science and Zoology, Molecular Biology, Cardiology and Cardiovascular Medicine and Biomaterials, having authored 36 papers that have together received 4.9k indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (16 papers), COVID-19 Clinical Research Studies (9 papers), Animal Virus Infections Studies (7 papers), Viral gastroenteritis research and epidemiology (3 papers), Collagen: Extraction and Characterization (3 papers), Marine Biology and Environmental Chemistry (2 papers), Antiplatelet Therapy and Cardiovascular Diseases (2 papers) and Berberine and alkaloids research (2 papers). The work is most often cited by research in Infectious Diseases (3.6k citations), Animal Science and Zoology (469 citations), Computational Theory and Mathematics (666 citations), Neurology (343 citations) and Modeling and Simulation (96 citations). Jun Lan has collaborated with scholars based in China, United States and South Korea. Frequent co-authors include Xinquan Wang, Linqi Zhang, Shilong Fan, Jinfang Yu, Sisi Shan, Jiwan Ge, Xuanling Shi, Qi Zhang, Huan Zhou and Qisheng Wang. Their work appears in journals such as Nature Communications, Structure, mBio, Frontiers in Immunology and PLoS Pathogens.
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.