Can Wu
Impact in
- Nephrology top 5%
- Chronic Kidney Disease and Diabetes
- Geriatrics and Gerontology top 5%
- Sirtuins and Resveratrol in Medicine
Papers in
-
- Metabolism, Diabetes, and Cancer 3
- Circular RNAs in diseases 2
-
- MicroRNA in disease regulation 5
- Cancer-related molecular mechanisms research 3
- Co-authors
- Qiuyue Wang (13 shared papers)Chuan Lv (11 shared papers)Xiaoyu Ma (5 shared papers)Ying Shao (7 shared papers)Huiwen Ren (6 shared papers)Ying Shao (4 shared papers)Yuehong Zhou (4 shared papers)Fenqin Chen (2 shared papers)
- Journals
- Diabetes/Metabolism Research and Reviews (2 papers)Molecular and Cellular Endocrinology (2 papers)Frontiers of Medicine (1 paper)Frontiers in Molecular Biosciences (1 paper)Experimental and Clinical Endocrinology & Diabetes (1 paper)
- Partner nations
- China
In The Last Decade
Can Wu
15 papers receiving 698 citations
Peers
Comparison fields: 5 of 79
- Nephrology 172
- Geriatrics and Gerontology 62
- Cancer Research 195
- Clinical Biochemistry 66
- Physiology 28
Countries citing papers authored by Can Wu
This map shows the geographic impact of Can Wu'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 Can Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Can Wu more than expected).
Fields of papers citing papers by Can Wu
This network shows the impact of papers produced by Can Wu. 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 Can Wu. The network helps show where Can Wu may publish in the future.
Co-authors
The 21 scholars most cited alongside Can Wu, 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 | 2019 | 244 | |
| 2 | 2016 | 86 | |
| 3 | 2014 | 62 | |
| 4 | 2015 | 57 | |
| 5 | 2016 | 49 | |
| 6 | 2016 | 47 | |
| 7 | 2015 | 44 | |
| 8 | 2018 | 30 | |
| 9 | 2014 | 24 | |
| 10 | 2020 | 20 | |
| 11 | 2014 | 16 | |
| 12 | 2018 | 16 | |
| 13 | 2020 | 13 | |
| 14 | 2016 | 1 | |
| 15 | 2022 | 1 |
About Can Wu
Can Wu is a scholar working on Molecular Biology, Cancer Research, Nephrology, Surgery and Pathology and Forensic Medicine, having authored 15 papers that have together received 710 indexed citations. Recurring topics across this work include MicroRNA in disease regulation (5 papers), Chronic Kidney Disease and Diabetes (4 papers), Metabolism, Diabetes, and Cancer (3 papers), Parathyroid Disorders and Treatments (3 papers), Cancer-related molecular mechanisms research (3 papers), Biomedical Research and Pathophysiology (2 papers), Circular RNAs in diseases (2 papers) and Diabetes, Cardiovascular Risks, and Lipoproteins (1 paper). The work is most often cited by research in Nephrology (172 citations), Geriatrics and Gerontology (62 citations), Cancer Research (195 citations), Clinical Biochemistry (66 citations) and Physiology (28 citations). Can Wu has collaborated with scholars based in China. Frequent co-authors include Qiuyue Wang, Chuan Lv, Xiaoyu Ma, Ying Shao, Huiwen Ren, Ying Shao, Yuehong Zhou, Fenqin Chen, Lei Sha and Guan Wang. Their work appears in journals such as Diabetes/Metabolism Research and Reviews, Molecular and Cellular Endocrinology, Frontiers of Medicine, Frontiers in Molecular Biosciences and Experimental and Clinical Endocrinology & Diabetes.
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.