Weiyong Liu
Impact in
- Infectious Diseases top 2%
- COVID-19 Clinical Research Studies
- SARS-CoV-2 and COVID-19 Research
- Obstetrics and Gynecology top 5%
- COVID-19 Impact on Reproduction
Papers in
-
- Bayesian Modeling and Causal Inference 6
- Topic Modeling 6
- Co-authors
- Jianguo Wu (21 shared papers)Chao Fu (15 shared papers)Yingle Liu (20 shared papers)Jun‐Ying Miao (8 shared papers)Bao‐Xiang Zhao (10 shared papers)Ziyong Sun (4 shared papers)Wenjun Chang (6 shared papers)Yanjun Lu (3 shared papers)
- Journals
- Journal of Virology (5 papers)PLoS ONE (3 papers)Poultry Science (2 papers)Information Sciences (2 papers)Knowledge-Based Systems (2 papers)
- Partner nations
- ChinaUnited StatesTaiwan
In The Last Decade
Weiyong Liu
96 papers receiving 2.8k citations
Peers
Comparison fields: 5 of 176
- Infectious Diseases 753
- Obstetrics and Gynecology 160
- Immunology 395
- Agronomy and Crop Science 139
- Hepatology 102
Countries citing papers authored by Weiyong Liu
This map shows the geographic impact of Weiyong Liu'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 Weiyong Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Weiyong Liu more than expected).
Fields of papers citing papers by Weiyong Liu
This network shows the impact of papers produced by Weiyong Liu. 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 Weiyong Liu. The network helps show where Weiyong Liu may publish in the future.
Co-authors
The 25 scholars most cited alongside Weiyong Liu, 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 99 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 372 | |
| 2 | 2020 | 173 | |
| 3 | 2020 | 172 | |
| 4 | 2014 | 123 | |
| 5 | Coronavirus Disease 2019 (COVID-19) During Pregnancy: A Case Series | 2020 | 115 |
| 6 | 2014 | 111 | |
| 7 | 2011 | 75 | |
| 8 | 2009 | 72 | |
| 9 | 2007 | 71 | |
| 10 | 2011 | 68 | |
| 11 | 2011 | 65 | |
| 12 | 2020 | 60 | |
| 13 | 2019 | 59 | |
| 14 | 2009 | 57 | |
| 15 | 2009 | 55 | |
| 16 | 2012 | 52 | |
| 17 | 2018 | 52 | |
| 18 | 2019 | 51 | |
| 19 | 2012 | 49 | |
| 20 | Enhanced expression of long noncoding RNA CARLo-5 is associated with the development of gastric cancer. | 2014 | 49 |
About Weiyong Liu
Weiyong Liu is a scholar working on Molecular Biology, Artificial Intelligence, Infectious Diseases, Surgery and Epidemiology, having authored 99 papers that have together received 2.9k indexed citations. Recurring topics across this work include Rough Sets and Fuzzy Logic (11 papers), Multi-Criteria Decision Making (7 papers), Hepatitis C virus research (7 papers), Tissue Engineering and Regenerative Medicine (6 papers), Bayesian Modeling and Causal Inference (6 papers), Topic Modeling (6 papers), Hepatitis B Virus Studies (5 papers) and Viral Infections and Immunology Research (5 papers). The work is most often cited by research in Infectious Diseases (753 citations), Obstetrics and Gynecology (160 citations), Immunology (395 citations), Agronomy and Crop Science (139 citations) and Hepatology (102 citations). Weiyong Liu has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include Jianguo Wu, Chao Fu, Yingle Liu, Jun‐Ying Miao, Bao‐Xiang Zhao, Ziyong Sun, Wenjun Chang, Yanjun Lu, Wenbiao Wang and Feng Wang. Their work appears in journals such as Journal of Virology, PLoS ONE, Poultry Science, Information Sciences and Knowledge-Based Systems.
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.