Dan Can
Impact in
- Neurology top 5%
- Neuroinflammation and Neurodegeneration Mechanisms
- Neurological Disease Mechanisms and Treatments
- Biological Psychiatry top 10%
- Tryptophan and brain disorders
Papers in ⓘ
-
- Neuroscience and Neuropharmacology Research 3
-
- Neuroinflammation and Neurodegeneration Mechanisms 5
- Neurological Disease Mechanisms and Treatments 2
- Co-authors
- Huaxi Xu (9 shared papers)Guojun Bu (4 shared papers)Xiao‐Fen Chen (4 shared papers)Daxin Wang (2 shared papers)Honghua Zheng (3 shared papers)Yun‐wu Zhang (7 shared papers)Li Zhong (3 shared papers)Zhaoji Liu (3 shared papers)
- Journals
- Journal of Neuroinflammation (2 papers)iScience (1 paper)Translational Neurodegeneration (1 paper)Frontiers in Aging Neuroscience (1 paper)Critical Reviews in Eukaryotic Gene Expression (1 paper)
- Partner nations
- ChinaUnited StatesTaiwan
In The Last Decade
Dan Can
15 papers receiving 456 citations
Peers
Comparison fields: 5 of 76
- Neurology 199
- Biological Psychiatry 38
- Physiology 152
- Developmental Neuroscience 24
- Immunology 108
Countries citing papers authored by Dan Can
This map shows the geographic impact of Dan Can'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 Dan Can with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dan Can more than expected).
Fields of papers citing papers by Dan Can
This network shows the impact of papers produced by Dan Can. 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 Dan Can. The network helps show where Dan Can may publish in the future.
Co-authors
The 25 scholars most cited alongside Dan Can, 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 | 2018 | 130 | |
| 2 | 2014 | 108 | |
| 3 | 2016 | 102 | |
| 4 | 2020 | 26 | |
| 5 | 2020 | 16 | |
| 6 | 2021 | 15 | |
| 7 | 2020 | 13 | |
| 8 | 2019 | 10 | |
| 9 | 2024 | 10 | |
| 10 | 2019 | 9 | |
| 11 | 2025 | 7 | |
| 12 | 2014 | 6 | |
| 13 | 2024 | 4 | |
| 14 | 2025 | 2 | |
| 15 | 2015 | 1 |
About Dan Can
Dan Can is a scholar working on Cellular and Molecular Neuroscience, Neurology, Physiology, Molecular Biology and Immunology, having authored 15 papers that have together received 459 indexed citations. Recurring topics across this work include Alzheimer's disease research and treatments (5 papers), Neuroinflammation and Neurodegeneration Mechanisms (5 papers), Inflammation biomarkers and pathways (4 papers), Neuroscience and Neuropharmacology Research (3 papers), Memory and Neural Mechanisms (2 papers), Neurological Disease Mechanisms and Treatments (2 papers), Machine Learning in Bioinformatics (1 paper) and MicroRNA in disease regulation (1 paper). The work is most often cited by research in Neurology (199 citations), Biological Psychiatry (38 citations), Physiology (152 citations), Developmental Neuroscience (24 citations) and Immunology (108 citations). Dan Can has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include Huaxi Xu, Guojun Bu, Xiao‐Fen Chen, Daxin Wang, Honghua Zheng, Yun‐wu Zhang, Li Zhong, Zhaoji Liu, Ying Xu and Takahisa Kanekiyo. Their work appears in journals such as Journal of Neuroinflammation, iScience, Translational Neurodegeneration, Frontiers in Aging Neuroscience and Critical Reviews in Eukaryotic Gene Expression.
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.