Jing Wu
Impact in
- Infectious Diseases top 1%
- Tuberculosis Research and Epidemiology
- SARS-CoV-2 and COVID-19 Research
- Cancer Research top 2%
- Cancer-related molecular mechanisms research
- MicroRNA in disease regulation
Papers in
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- RNA modifications and cancer 10
-
- Tuberculosis Research and Epidemiology 29
- SARS-CoV-2 and COVID-19 Research 8
- Co-authors
- Wenhong Zhang (24 shared papers)Peng Cui (11 shared papers)Lingyun Shao (33 shared papers)Michelle Gamber (4 shared papers)Jing Cai (3 shared papers)Guiqing He (3 shared papers)Jing Zhao (6 shared papers)Wenjie Sun (3 shared papers)
- Journals
- PLoS ONE (7 papers)Emerging Microbes & Infections (7 papers)Scientific Reports (5 papers)Frontiers in Immunology (5 papers)Frontiers in Microbiology (3 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Jing Wu
173 papers receiving 4.4k citations
Peers
Comparison fields: 5 of 158
- Infectious Diseases 1.1k
- Cancer Research 842
- Modeling and Simulation 130
- General Dentistry 39
- Immunology 490
Countries citing papers authored by Jing Wu
This map shows the geographic impact of Jing Wu'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 Jing Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jing Wu more than expected).
Fields of papers citing papers by Jing Wu
This network shows the impact of papers produced by Jing Wu. 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 Jing Wu. The network helps show where Jing Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Jing Wu, 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 182 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 410 | |
| 2 | 2018 | 284 | |
| 3 | 2016 | 222 | |
| 4 | 2015 | 193 | |
| 5 | 2020 | 147 | |
| 6 | 2017 | 128 | |
| 7 | 2020 | 114 | |
| 8 | 2017 | 106 | |
| 9 | 2011 | 101 | |
| 10 | 2016 | 96 | |
| 11 | 2013 | 86 | |
| 12 | 2022 | 85 | |
| 13 | 2012 | 77 | |
| 14 | 2019 | 74 | |
| 15 | 2011 | 73 | |
| 16 | 2015 | 71 | |
| 17 | 2018 | 61 | |
| 18 | Boosting NAD+ blunts TLR4-induced type I IFN in control and systemic lupus erythematosus monocytes | 2022 | 46 |
| 19 | 2016 | 46 | |
| 20 | 2021 | 46 |
About Jing Wu
Jing Wu is a scholar working on Molecular Biology, Infectious Diseases, Immunology, Epidemiology and Cancer Research, having authored 182 papers that have together received 4.4k indexed citations. Recurring topics across this work include Tuberculosis Research and Epidemiology (29 papers), Mycobacterium research and diagnosis (14 papers), Cancer-related molecular mechanisms research (11 papers), Immune Cell Function and Interaction (11 papers), Immunodeficiency and Autoimmune Disorders (10 papers), RNA modifications and cancer (10 papers), MicroRNA in disease regulation (8 papers) and SARS-CoV-2 and COVID-19 Research (8 papers). The work is most often cited by research in Infectious Diseases (1.1k citations), Cancer Research (842 citations), Modeling and Simulation (130 citations), General Dentistry (39 citations) and Immunology (490 citations). Jing Wu has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Wenhong Zhang, Peng Cui, Lingyun Shao, Michelle Gamber, Jing Cai, Guiqing He, Jing Zhao, Wenjie Sun, Jianping Huang and Wenhong Zhang. Their work appears in journals such as PLoS ONE, Emerging Microbes & Infections, Scientific Reports, Frontiers in Immunology and Frontiers in Microbiology.
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.