Wei-Chen Wu
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
- Viral Infections and Vectors
- Modeling and Simulation top 10%
Papers in
-
- Viral Infections and Vectors 8
- Viral gastroenteritis research and epidemiology 4
- Viral Infections and Outbreaks Research 3
-
- Vector-Borne Animal Diseases 3
- Co-authors
- Mǎng Shī (19 shared papers)Yirong Li (2 shared papers)Guangming Ye (2 shared papers)Liangjun Chen (2 shared papers)Weiyong Liu (1 shared paper)Fang Liu (1 shared paper)Bo Zhong (1 shared paper)Zhang Qi (1 shared paper)
In The Last Decade
Wei-Chen Wu
23 papers receiving 655 citations
Wei-Chen Wu's Hit Papers
Peers
Comparison fields: 5 of 99
- Infectious Diseases 372
- Modeling and Simulation 28
- Animal Science and Zoology 62
- Neurology 45
- General Dentistry 4
Countries citing papers authored by Wei-Chen Wu
This map shows the geographic impact of Wei-Chen 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 Wei-Chen Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wei-Chen Wu more than expected).
Fields of papers citing papers by Wei-Chen Wu
This network shows the impact of papers produced by Wei-Chen 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 Wei-Chen Wu. The network helps show where Wei-Chen Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Wei-Chen 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 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | RNA based mNGS approach identifies a novel human coronavirus from two individual pneumonia cases in 2019 Wuhan outbreak Hit paper breakdown → | 2020 | 414 |
| 2 | 2018 | 52 | |
| 3 | 2022 | 32 | |
| 4 | 2021 | 31 | |
| 5 | 2019 | 26 | |
| 6 | 2022 | 19 | |
| 7 | 2022 | 18 | |
| 8 | 2023 | 14 | |
| 9 | 2022 | 12 | |
| 10 | 2021 | 10 | |
| 11 | 2024 | 8 | |
| 12 | 2024 | 5 | |
| 13 | 2023 | 5 | |
| 14 | 2023 | 5 | |
| 15 | 2025 | 5 | |
| 16 | 2024 | 4 | |
| 17 | 2024 | 4 | |
| 18 | 2017 | 4 | |
| 19 | 2023 | 2 | |
| 20 | 2025 | 2 |
About Wei-Chen Wu
Wei-Chen Wu is a scholar working on Infectious Diseases, Ecology, Evolution, Behavior and Systematics, Ecology, Animal Science and Zoology and Epidemiology, having authored 26 papers that have together received 675 indexed citations. Recurring topics across this work include Viral Infections and Vectors (8 papers), Viral gastroenteritis research and epidemiology (4 papers), Bacteriophages and microbial interactions (4 papers), Animal Virus Infections Studies (4 papers), Vector-Borne Animal Diseases (3 papers), Animal Disease Management and Epidemiology (3 papers), Viral Infections and Outbreaks Research (3 papers) and Rabies epidemiology and control (2 papers). The work is most often cited by research in Infectious Diseases (372 citations), Modeling and Simulation (28 citations), Animal Science and Zoology (62 citations), Neurology (45 citations) and General Dentistry (4 citations). Wei-Chen Wu has collaborated with scholars based in China, Australia and Hong Kong. Frequent co-authors include Mǎng Shī, Yirong Li, Guangming Ye, Liangjun Chen, Weiyong Liu, Fang Liu, Bo Zhong, Zhang Qi, Ziyong Sun and Wenxia Zhang. Their work appears in journals such as Viruses, Virus Evolution, PLoS Pathogens, Carbon and Microbiome.
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.