Xufang Deng
- Infectious Diseases top 1%
- Molecular Biology
- Immunology top 10%
- Animal Science and Zoology top 2%
- Computational Theory and Mathematics top 2%
- Co-authors
- Susan C. BakerMatthew HackbartAnna M. MielechAmornrat O’BrienRobert C. MettelmanAndrew D. MesecarC. Cheng KaoGuanghui Yi
- Topics
- SARS-CoV-2 and COVID-19 Research (20 papers)Animal Virus Infections Studies (9 papers)Thin-Film Transistor Technologies (9 papers)
- Partner nations
- United StatesChinaSwitzerland
In The Last Decade
Xufang Deng
45 papers receiving 1.7k citations
Hit Papers
Peers
Comparison fields: 5 of 96
- Infectious Diseases 1.1k
- Molecular Biology 456
- Immunology 378
- Animal Science and Zoology 347
- Computational Theory and Mathematics 279
Countries citing papers authored by Xufang Deng
This map shows the geographic impact of Xufang Deng'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 Xufang Deng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xufang Deng more than expected).
Fields of papers citing papers by Xufang Deng
This network shows the impact of papers produced by Xufang Deng. 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 Xufang Deng. The network helps show where Xufang Deng may publish in the future.
Co-authorship network of co-authors of Xufang Deng
This figure shows the co-authorship network connecting the top 25 collaborators of Xufang Deng. A scholar is included among the top collaborators of Xufang Deng 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 Xufang Deng. Xufang Deng 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 | 1 | |
| 3 | 1 | |
| 4 | 3 | |
| 5 | 2 | |
| 6 | 8 | |
| 7 | Design of a SARS-CoV-2 papain-like protease inhibitor with antiviral efficacy in a mouse modelbreakdown → | 43 |
| 8 | Naturally Occurring Mutations of SARS-CoV-2 Main Protease Confer Drug Resistance to Nirmatrelvirbreakdown → | 167 |
| 9 | 12 | |
| 10 | 0 | |
| 11 | 18 | |
| 12 | 7 | |
| 13 | 110 | |
| 14 | 34 | |
| 15 | 59 | |
| 16 | 91 | |
| 17 | 48 | |
| 18 | 5 | |
| 19 | 3 | |
| 20 | 2 |
About Xufang Deng
Xufang Deng is a scholar working on Infectious Diseases, Animal Science and Zoology and Virology, having authored 48 papers that have together received 1.8k indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (20 papers), Animal Virus Infections Studies (9 papers) and Thin-Film Transistor Technologies (9 papers). The work is most often cited by research in Infectious Diseases (1.1k citations), Animal Science and Zoology (347 citations) and Immunology (378 citations). Xufang Deng has collaborated with scholars based in United States, China and Switzerland. Frequent co-authors include Susan C. Baker, Matthew Hackbart, Anna M. Mielech, Amornrat O’Brien, Robert C. Mettelman, Andrew D. Mesecar, C. Cheng Kao, Guanghui Yi, Andy Kilianski and Zixue Shi. Their work appears in journals such as Science, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.
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.