Yingxia Liu
- Infectious Diseases top 0.5%
- Epidemiology top 2%
- Molecular Biology top 10%
- Neurology top 1%
- Oncology top 5%
- Co-authors
- Lei LiuJia XiaoZhaoqin WangJun ChenLin XuQing HeQingxian CaiJing Yuan
- Topics
- COVID-19 Clinical Research Studies (25 papers)SARS-CoV-2 and COVID-19 Research (23 papers)Liver Disease Diagnosis and Treatment (23 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of the American Chemical SocietyNature Communications
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Yingxia Liu
180 papers receiving 5.6k citations
Hit Papers
Peers
Comparison fields: 5 of 185
- Infectious Diseases 2.3k
- Epidemiology 1.4k
- Molecular Biology 1.0k
- Neurology 802
- Oncology 475
Countries citing papers authored by Yingxia Liu
This map shows the geographic impact of Yingxia 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 Yingxia Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yingxia Liu more than expected).
Fields of papers citing papers by Yingxia Liu
This network shows the impact of papers produced by Yingxia 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 Yingxia Liu. The network helps show where Yingxia Liu may publish in the future.
Co-authorship network of co-authors of Yingxia Liu
This figure shows the co-authorship network connecting the top 25 collaborators of Yingxia Liu. A scholar is included among the top collaborators of Yingxia Liu 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 Yingxia Liu. Yingxia Liu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | Ultrasensitive DNA Origami Plasmon Sensor for Accurate Detection in Circulating Tumor DNAsbreakdown → | 89 |
| 3 | 9 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 12 | |
| 8 | 7 | |
| 9 | 2 | |
| 10 | 1 | |
| 11 | 6 | |
| 12 | 236 | |
| 13 | 12 | |
| 14 | 44 | |
| 15 | Obesity and COVID-19 Severity in a Designated Hospital in Shenzhen, Chinabreakdown → | 483 |
| 16 | COVID-19: Abnormal liver function testsbreakdown → | 708 |
| 17 | 17 | |
| 18 | 72 | |
| 19 | 20 | |
| 20 | 20 |
About Yingxia Liu
Yingxia Liu is a scholar working on Infectious Diseases, Hepatology and Epidemiology, having authored 188 papers that have together received 5.7k indexed citations. Recurring topics across this work include COVID-19 Clinical Research Studies (25 papers), SARS-CoV-2 and COVID-19 Research (23 papers) and Liver Disease Diagnosis and Treatment (23 papers). The work is most often cited by research in Infectious Diseases (2.3k citations), Modeling and Simulation (363 citations) and Hepatology (453 citations). Yingxia Liu has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Lei Liu, Jia Xiao, Zhaoqin Wang, Jun Chen, Lin Xu, Qing He, Qingxian Cai, Jing Yuan, Kwok‐Fai So and Yuhai Bi. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Nature Communications.
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.