Faming Zhao
Impact in
- Infectious Diseases top 1%
- COVID-19 Clinical Research Studies
- SARS-CoV-2 and COVID-19 Research
- Neurology top 2%
- Long-Term Effects of COVID-19
Papers in
-
- Single-cell and spatial transcriptomics 2
-
- Ferroptosis and cancer prognosis 5
- Co-authors
- Yunhe Zhao (1 shared paper)Jing Yang (2 shared papers)Xiqian Wang (1 shared paper)Lin Liu (1 shared paper)Bo Li (1 shared paper)Lili Zhi (1 shared paper)Tingting Zhang (9 shared papers)Xia Sheng (9 shared papers)
- Journals
- Theranostics (3 papers)Computers in Biology and Medicine (2 papers)Oncogene (2 papers)Cell Genomics (1 paper)Frontiers in Cell and Developmental Biology (1 paper)
- Partner nations
- ChinaUnited StatesNorway
In The Last Decade
Faming Zhao
21 papers receiving 1.5k citations
Faming Zhao's Hit Papers
Peers
Comparison fields: 5 of 110
- Infectious Diseases 1.0k
- Neurology 590
- Oncology 350
- Modeling and Simulation 56
- Biological Psychiatry 24
Countries citing papers authored by Faming Zhao
This map shows the geographic impact of Faming Zhao'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 Faming Zhao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Faming Zhao more than expected).
Fields of papers citing papers by Faming Zhao
This network shows the impact of papers produced by Faming Zhao. 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 Faming Zhao. The network helps show where Faming Zhao may publish in the future.
Co-authors
The 25 scholars most cited alongside Faming Zhao, 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 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Prevalence and impact of cardiovascular metabolic diseases on COVID-19 in China Hit paper breakdown → | 2020 | 1405 |
| 2 | 2020 | 24 | |
| 3 | 2024 | 23 | |
| 4 | 2021 | 23 | |
| 5 | 2021 | 21 | |
| 6 | 2020 | 15 | |
| 7 | 2024 | 11 | |
| 8 | 2015 | 11 | |
| 9 | 2023 | 11 | |
| 10 | 2024 | 8 | |
| 11 | 2023 | 7 | |
| 12 | 2023 | 6 | |
| 13 | 2020 | 5 | |
| 14 | 2025 | 4 | |
| 15 | 2020 | 4 | |
| 16 | 2024 | 3 | |
| 17 | 2023 | 2 | |
| 18 | 2024 | 2 | |
| 19 | 2024 | 2 | |
| 20 | 2025 | 2 |
About Faming Zhao
Faming Zhao is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine, Immunology, Oncology and Neurology, having authored 24 papers that have together received 1.6k indexed citations. Recurring topics across this work include Ferroptosis and cancer prognosis (5 papers), Neuroinflammation and Neurodegeneration Mechanisms (4 papers), Cancer Immunotherapy and Biomarkers (3 papers), Immune cells in cancer (3 papers), Single-cell and spatial transcriptomics (2 papers), Neurogenesis and neuroplasticity mechanisms (2 papers), Cancer, Lipids, and Metabolism (2 papers) and Endoplasmic Reticulum Stress and Disease (2 papers). The work is most often cited by research in Infectious Diseases (1.0k citations), Neurology (590 citations), Oncology (350 citations), Modeling and Simulation (56 citations) and Biological Psychiatry (24 citations). Faming Zhao has collaborated with scholars based in China, United States and Norway. Frequent co-authors include Yunhe Zhao, Jing Yang, Xiqian Wang, Lin Liu, Bo Li, Lili Zhi, Tingting Zhang, Xia Sheng, Fengzhen Cui and Jihua Shi. Their work appears in journals such as Theranostics, Computers in Biology and Medicine, Oncogene, Cell Genomics and Frontiers in Cell and Developmental Biology.
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.