Quan Fang
- Molecular Biology top 5%
- Cardiology and Cardiovascular Medicine top 5%
- Cellular and Molecular Neuroscience top 2%
- Physiology top 5%
- Surgery top 10%
- Co-authors
- Zhuang TianZhongwei ChengZilong WangCarola A. NeumannLei ZhaoYuanqiang ZhangChunmao HanSongxue Guo
- Topics
- Neuropeptides and Animal Physiology (46 papers)Receptor Mechanisms and Signaling (34 papers)Pain Mechanisms and Treatments (27 papers)
- Journals
- Journal of Biological ChemistrySHILAP Revista de lepidopterologíaJournal of the American College of Cardiology
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Quan Fang
265 papers receiving 3.9k citations
Peers
Comparison fields: 5 of 139
- Molecular Biology 1.6k
- Cardiology and Cardiovascular Medicine 656
- Cellular and Molecular Neuroscience 652
- Physiology 642
- Surgery 424
Countries citing papers authored by Quan Fang
This map shows the geographic impact of Quan Fang'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 Quan Fang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Quan Fang more than expected).
Fields of papers citing papers by Quan Fang
This network shows the impact of papers produced by Quan Fang. 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 Quan Fang. The network helps show where Quan Fang may publish in the future.
Co-authorship network of co-authors of Quan Fang
This figure shows the co-authorship network connecting the top 25 collaborators of Quan Fang. A scholar is included among the top collaborators of Quan Fang 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 Quan Fang. Quan Fang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 6 | |
| 4 | 0 | |
| 5 | 3 | |
| 6 | 2 | |
| 7 | 16 | |
| 8 | 5 | |
| 9 | 3 | |
| 10 | 6 | |
| 11 | 5 | |
| 12 | 28 | |
| 13 | 25 | |
| 14 | 8 | |
| 15 | 1 | |
| 16 | 10 | |
| 17 | 1 | |
| 18 | 39 | |
| 19 | P53 enhances ascorbyl stearate-induced G2/M arrest of human ovarian cancer cells. | 10 |
| 20 | The meningioma diagnostic value with digital subtraction cerebral angiography | 1 |
About Quan Fang
Quan Fang is a scholar working on Cardiology and Cardiovascular Medicine, Cellular and Molecular Neuroscience and Nephrology, having authored 280 papers that have together received 3.9k indexed citations. Recurring topics across this work include Neuropeptides and Animal Physiology (46 papers), Receptor Mechanisms and Signaling (34 papers) and Pain Mechanisms and Treatments (27 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (652 citations), Nephrology (212 citations) and Cardiology and Cardiovascular Medicine (656 citations). Quan Fang has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Zhuang Tian, Zhongwei Cheng, Zilong Wang, Carola A. Neumann, Lei Zhao, Yuanqiang Zhang, Chunmao Han, Songxue Guo, Rui Wang and Mengna Zhang. Their work appears in journals such as Journal of Biological Chemistry, SHILAP Revista de lepidopterología and Journal of the American College of Cardiology.
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.