Dan‐yun Lai
Impact in
- Infectious Diseases top 5%
- 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 10%
- Animal Virus Infections Studies
Papers in
-
- SARS-CoV-2 and COVID-19 Research 13
- SARS-CoV-2 detection and testing 6
- COVID-19 Clinical Research Studies 2
-
- Animal Virus Infections Studies 4
- Co-authors
- Sheng‐ce Tao (9 shared papers)Huan Yang Qi (6 shared papers)Shujuan Guo (5 shared papers)Ming‐liang Ma (5 shared papers)He‐wei Jiang (6 shared papers)Hainan Zhang (4 shared papers)Qingfeng Meng (3 shared papers)Wei Wang (1 shared paper)
- Journals
- Cellular and Molecular Immunology (3 papers)Molecular & Cellular Proteomics (2 papers)Cell Discovery (2 papers)Cell Reports (2 papers)Allergy (1 paper)
- Partner nations
- ChinaUnited States
In The Last Decade
Dan‐yun Lai
16 papers receiving 564 citations
Peers
Comparison fields: 5 of 56
- Infectious Diseases 408
- Animal Science and Zoology 77
- Modeling and Simulation 19
- Radiology, Nuclear Medicine and Imaging 86
- Immunology 75
Countries citing papers authored by Dan‐yun Lai
This map shows the geographic impact of Dan‐yun Lai'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 Dan‐yun Lai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dan‐yun Lai more than expected).
Fields of papers citing papers by Dan‐yun Lai
This network shows the impact of papers produced by Dan‐yun Lai. 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 Dan‐yun Lai. The network helps show where Dan‐yun Lai may publish in the future.
Co-authors
The 25 scholars most cited alongside Dan‐yun Lai, 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 | 129 | |
| 2 | 2021 | 121 | |
| 3 | 2020 | 98 | |
| 4 | 2021 | 42 | |
| 5 | 2020 | 39 | |
| 6 | 2021 | 32 | |
| 7 | 2021 | 26 | |
| 8 | 2019 | 20 | |
| 9 | 2021 | 13 | |
| 10 | 2022 | 13 | |
| 11 | 2022 | 12 | |
| 12 | 2021 | 9 | |
| 13 | 2021 | 7 | |
| 14 | 2021 | 5 | |
| 15 | 2022 | 3 | |
| 16 | 2022 | 2 | |
| 17 | 2025 | 0 |
About Dan‐yun Lai
Dan‐yun Lai is a scholar working on Infectious Diseases, Animal Science and Zoology, Radiology, Nuclear Medicine and Imaging, Molecular Biology and Immunology, having authored 17 papers that have together received 571 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (13 papers), SARS-CoV-2 detection and testing (6 papers), Animal Virus Infections Studies (4 papers), vaccines and immunoinformatics approaches (4 papers), Monoclonal and Polyclonal Antibodies Research (3 papers), COVID-19 Clinical Research Studies (2 papers), Advanced Biosensing Techniques and Applications (2 papers) and Biosensors and Analytical Detection (2 papers). The work is most often cited by research in Infectious Diseases (408 citations), Animal Science and Zoology (77 citations), Modeling and Simulation (19 citations), Radiology, Nuclear Medicine and Imaging (86 citations) and Immunology (75 citations). Dan‐yun Lai has collaborated with scholars based in China and United States. Frequent co-authors include Sheng‐ce Tao, Huan Yang Qi, Shujuan Guo, Ming‐liang Ma, He‐wei Jiang, Hainan Zhang, Qingfeng Meng, Wei Wang, Junbiao Dai and Yanling Wu. Their work appears in journals such as Cellular and Molecular Immunology, Molecular & Cellular Proteomics, Cell Discovery, Cell Reports and Allergy.
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.