Xiaoshan Su
Impact in
- Infectious Diseases top 5%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
- SARS-CoV-2 detection and testing
- Modeling and Simulation top 5%
- COVID-19 epidemiological studies
Papers in
-
- RNA modifications and cancer 1
- Epigenetics and DNA Methylation 1
- Genomics, phytochemicals, and oxidative stress 1
- Inflammasome and immune disorders 1
- Oncology 2
- Co-authors
- Zhixing Zhu (9 shared papers)Weijing Wu (8 shared papers)Yiming Zeng (9 shared papers)Xihua Lian (3 shared papers)Giuseppe A. Marraro (1 shared paper)Xiaoping Lin (4 shared papers)Qiangqiang Sun (1 shared paper)Zenglin Wang (1 shared paper)
In The Last Decade
Xiaoshan Su
13 papers receiving 629 citations
Xiaoshan Su's Hit Papers
Peers
Comparison fields: 5 of 110
- Infectious Diseases 258
- Modeling and Simulation 39
- Neurology 48
- Critical Care and Intensive Care Medicine 15
- Pulmonary and Respiratory Medicine 82
Countries citing papers authored by Xiaoshan Su
This map shows the geographic impact of Xiaoshan Su'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 Xiaoshan Su with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaoshan Su more than expected).
Fields of papers citing papers by Xiaoshan Su
This network shows the impact of papers produced by Xiaoshan Su. 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 Xiaoshan Su. The network helps show where Xiaoshan Su may publish in the future.
Co-authors
The 25 scholars most cited alongside Xiaoshan Su, 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 | From SARS and MERS to COVID-19: a brief summary and comparison of severe acute respiratory infections caused by three highly pathogenic human coronaviruses Hit paper breakdown → | 2020 | 434 |
| 2 | 2022 | 45 | |
| 3 | 2022 | 38 | |
| 4 | 2017 | 33 | |
| 5 | 2021 | 22 | |
| 6 | 2021 | 21 | |
| 7 | 2019 | 15 | |
| 8 | 2021 | 11 | |
| 9 | 2022 | 5 | |
| 10 | 2023 | 5 | |
| 11 | 2021 | 4 | |
| 12 | 2023 | 3 | |
| 13 | 2023 | 1 | |
| 14 | 2023 | 0 | |
| 15 | 2025 | 0 |
About Xiaoshan Su
Xiaoshan Su is a scholar working on Molecular Biology, Oncology, Immunology, Cancer Research and Infectious Diseases, having authored 15 papers that have together received 637 indexed citations. Recurring topics across this work include interferon and immune responses (1 paper), RNA modifications and cancer (1 paper), Epigenetics and DNA Methylation (1 paper), Cancer Genomics and Diagnostics (1 paper), Cancer-related molecular mechanisms research (1 paper), Hemodynamic Monitoring and Therapy (1 paper), Genomics, phytochemicals, and oxidative stress (1 paper) and Inflammasome and immune disorders (1 paper). The work is most often cited by research in Infectious Diseases (258 citations), Modeling and Simulation (39 citations), Neurology (48 citations), Critical Care and Intensive Care Medicine (15 citations) and Pulmonary and Respiratory Medicine (82 citations). Xiaoshan Su has collaborated with scholars based in China, Australia and Italy. Frequent co-authors include Zhixing Zhu, Weijing Wu, Yiming Zeng, Xihua Lian, Giuseppe A. Marraro, Xiaoping Lin, Qiangqiang Sun, Zenglin Wang, Jingjing Bai and Chuan Zhao. Their work appears in journals such as Respiratory Research, Computational and Structural Biotechnology Journal, BMC Medical Genomics, International Immunopharmacology and Toxicology in Vitro.
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.