Q Li
- Molecular Biology
- Cardiology and Cardiovascular Medicine top 5%
- Surgery
- Endocrinology, Diabetes and Metabolism top 10%
- Pathology and Forensic Medicine
- Co-authors
- Annarosa LeriPiero AnversaJan KajsturaB LiXiaohui WangRenato BasergaKrzysztof ReissShanshan Wang
- Topics
- Cardiac Fibrosis and Remodeling (2 papers)Cardiovascular, Neuropeptides, and Oxidative Stress Research (1 paper)Coagulation, Bradykinin, Polyphosphates, and Angioedema (1 paper)
- Cited by
- Cardiology and Cardiovascular MedicineEndocrinology, Diabetes and MetabolismMolecular Biology
- Journals
- Journal of Clinical InvestigationClinical and Experimental Pharmacology and PhysiologyInternational Journal of Clinical Practice
- Partner nations
- ChinaUnited StatesNetherlands
In The Last Decade
Q Li
6 papers receiving 807 citations
Peers
Comparison fields: 5 of 74
- Molecular Biology 464
- Cardiology and Cardiovascular Medicine 395
- Surgery 151
- Endocrinology, Diabetes and Metabolism 136
- Pathology and Forensic Medicine 110
Countries citing papers authored by Q Li
This map shows the geographic impact of Q Li'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 Q Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Q Li more than expected).
Fields of papers citing papers by Q Li
This network shows the impact of papers produced by Q Li. 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 Q Li. The network helps show where Q Li may publish in the future.
Co-authorship network of co-authors of Q Li
This figure shows the co-authorship network connecting the top 25 collaborators of Q Li. A scholar is included among the top collaborators of Q Li 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 Q Li. Q Li 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 | 0 | |
| 3 | 32 | |
| 4 | 13 | |
| 5 | INSERTION/DELETION POLYMORPHISM OF THE ACE GENE IS ASSOCIATED WITH T2D | 1 |
| 6 | 5 | |
| 7 | 375 | |
| 8 | Relationship between angiotensin I converting enzyme gene polymorphism and diabetic nephropathy. | 6 |
| 9 | 390 |
About Q Li
Q Li is a scholar working on Nephrology, Cardiology and Cardiovascular Medicine and Genetics, having authored 9 papers that have together received 822 indexed citations. Recurring topics across this work include Cardiac Fibrosis and Remodeling (2 papers), Cardiovascular, Neuropeptides, and Oxidative Stress Research (1 paper) and Coagulation, Bradykinin, Polyphosphates, and Angioedema (1 paper). The work is most often cited by research in Cardiology and Cardiovascular Medicine (395 citations), Endocrinology, Diabetes and Metabolism (136 citations) and Molecular Biology (464 citations). Q Li has collaborated with scholars based in China, United States and Netherlands. Frequent co-authors include Annarosa Leri, Piero Anversa, Jan Kajstura, B Li, Xiaohui Wang, Renato Baserga, Krzysztof Reiss, Shanshan Wang, Xiaodong Wang and Pier Paolo Claudio. Their work appears in journals such as Journal of Clinical Investigation, Clinical and Experimental Pharmacology and Physiology and International Journal of Clinical Practice.
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.