Shibo Jiang
Impact in
- Infectious Diseases top 0.01%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
- Viral gastroenteritis research and epidemiology
- HIV/AIDS drug development and treatment
- Virology top 0.05%
- HIV Research and Treatment
Papers in
- Virology 190
- HIV Research and Treatment 188
-
- SARS-CoV-2 and COVID-19 Research 161
- HIV/AIDS drug development and treatment 134
- COVID-19 Clinical Research Studies 67
- Viral gastroenteritis research and epidemiology 63
Shibo Jiang
481 papers receiving 28.2k citations
Hit Papers
Peers
Comparison fields: 5 of 192
- Infectious Diseases 19.6k
- Virology 4.5k
- Animal Science and Zoology 3.8k
- Immunology 4.1k
- Modeling and Simulation 796
Countries citing papers authored by Shibo Jiang
This map shows the geographic impact of Shibo Jiang'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 Shibo Jiang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shibo Jiang more than expected).
Fields of papers citing papers by Shibo Jiang
This network shows the impact of papers produced by Shibo Jiang. 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 Shibo Jiang. The network helps show where Shibo Jiang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Shibo Jiang, 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 | 2024 | 2 | |
| 2 | 2024 | 1 | |
| 3 | 2023 | 3 | |
| 4 | 2023 | 4 | |
| 5 | 2023 | 40 | |
| 6 | 2023 | 16 | |
| 7 | 2021 | 13 | |
| 8 | 2020 | 237 | |
| 9 | 2020 | 11 | |
| 10 | Potent binding of 2019 novel coronavirus spike protein by a SARS coronavirus-specific human monoclonal antibody Hit paper breakdown → | 2020 | 838 |
| 11 | Antiviral Agent Therapy Optimization in Special Populations of COVID-19 Patients | 2020 | 1 |
| 12 | 2020 | 228 | |
| 13 | 2019 | 17 | |
| 14 | 2018 | 38 | |
| 15 | 2018 | 40 | |
| 16 | 2017 | 95 | |
| 17 | 2015 | 65 | |
| 18 | 2013 | 14 | |
| 19 | 2011 | 2 | |
| 20 | 2003 | 12 |
About Shibo Jiang
Shibo Jiang is a scholar working on Virology, Infectious Diseases, Animal Science and Zoology, Immunology and Microbiology, having authored 496 papers that have together received 28.8k indexed citations. Recurring topics across this work include HIV Research and Treatment (188 papers), SARS-CoV-2 and COVID-19 Research (161 papers), HIV/AIDS drug development and treatment (134 papers), Animal Virus Infections Studies (84 papers), COVID-19 Clinical Research Studies (67 papers), Viral gastroenteritis research and epidemiology (63 papers), Influenza Virus Research Studies (59 papers) and Monoclonal and Polyclonal Antibodies Research (58 papers). The work is most often cited by research in Infectious Diseases (19.6k citations), Virology (4.5k citations), Animal Science and Zoology (3.8k citations), Immunology (4.1k citations) and Modeling and Simulation (796 citations). Shibo Jiang has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Lanying Du, Shuwen Liu, Yusen Zhou, Lu Lu, Yuxian He, Hong Lü, Asim K. Debnath, Shuai Xia, Zheng‐Li Shi and Tianlei Ying. Their work appears in journals such as Viruses, Journal of Virology, Microbes and Infection, Biochemical and Biophysical Research Communications and Journal of Medicinal 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.