Tianlei Ying
- Infectious Diseases top 0.5%
- Molecular Biology top 5%
- Radiology, Nuclear Medicine and Imaging top 1%
- Immunology top 5%
- Oncology top 5%
- Co-authors
- Shibo JiangYanling WuLu LuShuai XiaDimiter S. DimitrovZheng‐Li ShiZhenlin YangXiaolong Tian
- Topics
- Monoclonal and Polyclonal Antibodies Research (48 papers)SARS-CoV-2 and COVID-19 Research (30 papers)Glycosylation and Glycoproteins Research (17 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of the American Chemical SocietyAdvanced Materials
- Partner nations
- ChinaUnited StatesNew Zealand
In The Last Decade
Tianlei Ying
131 papers receiving 4.8k citations
Hit Papers
Peers
Comparison fields: 5 of 143
- Infectious Diseases 2.6k
- Molecular Biology 1.7k
- Radiology, Nuclear Medicine and Imaging 955
- Immunology 762
- Oncology 481
Countries citing papers authored by Tianlei Ying
This map shows the geographic impact of Tianlei Ying'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 Tianlei Ying with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tianlei Ying more than expected).
Fields of papers citing papers by Tianlei Ying
This network shows the impact of papers produced by Tianlei Ying. 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 Tianlei Ying. The network helps show where Tianlei Ying may publish in the future.
Co-authorship network of co-authors of Tianlei Ying
This figure shows the co-authorship network connecting the top 25 collaborators of Tianlei Ying. A scholar is included among the top collaborators of Tianlei Ying based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Tianlei Ying. Tianlei Ying is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 12 | |
| 7 | 9 | |
| 8 | 25 | |
| 9 | 5 | |
| 10 | 64 | |
| 11 | 96 | |
| 12 | Potent binding of 2019 novel coronavirus spike protein by a SARS coronavirus-specific human monoclonal antibodybreakdown → | 838 |
| 13 | 33 | |
| 14 | 115 | |
| 15 | 77 | |
| 16 | 49 | |
| 17 | 47 | |
| 18 | 43 | |
| 19 | 25 | |
| 20 | 54 |
About Tianlei Ying
Tianlei Ying is a scholar working on Virology, Infectious Diseases and Radiology, Nuclear Medicine and Imaging, having authored 140 papers that have together received 4.9k indexed citations. Recurring topics across this work include Monoclonal and Polyclonal Antibodies Research (48 papers), SARS-CoV-2 and COVID-19 Research (30 papers) and Glycosylation and Glycoproteins Research (17 papers). The work is most often cited by research in Infectious Diseases (2.6k citations), Animal Science and Zoology (435 citations) and Virology (197 citations). Tianlei Ying has collaborated with scholars based in China, United States and New Zealand. Frequent co-authors include Shibo Jiang, Yanling Wu, Lu Lu, Shuai Xia, Dimiter S. Dimitrov, Zheng‐Li Shi, Zhenlin Yang, Xiaolong Tian, Ailing Huang and Cheng Li. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Advanced Materials.
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.