Tingjun Dai
Impact in
- Clinical Biochemistry top 5%
- Metabolism and Genetic Disorders
Papers in ⓘ
- Epidemiology 24
- Inflammatory Myopathies and Dermatomyositis 21
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- Muscle Physiology and Disorders 10
- Co-authors
- Chuanzhu Yan (29 shared papers)Ying Hou (13 shared papers)Yuying Zhao (14 shared papers)Pengfei Lin (9 shared papers)Wei Li (2 shared papers)Bing Wen (2 shared papers)Haihong Zheng (1 shared paper)Yanyan Zhao (1 shared paper)
- Journals
- CNS Neuroscience & Therapeutics (3 papers)Neurological Sciences (2 papers)Arthritis Research & Therapy (2 papers)Journal of Neuropathology & Experimental Neurology (2 papers)Journal of Neurology (2 papers)
- Partner nations
- ChinaCanadaUnited States
In The Last Decade
Tingjun Dai
31 papers receiving 423 citations
Peers
Comparison fields: 5 of 62
- Clinical Biochemistry 82
- Neurology 75
- Epidemiology 152
- Cellular and Molecular Neuroscience 78
- Genetics 41
Countries citing papers authored by Tingjun Dai
This map shows the geographic impact of Tingjun Dai'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 Tingjun Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tingjun Dai more than expected).
Fields of papers citing papers by Tingjun Dai
This network shows the impact of papers produced by Tingjun Dai. 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 Tingjun Dai. The network helps show where Tingjun Dai may publish in the future.
Co-authors
The 25 scholars most cited alongside Tingjun Dai, 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 39 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2009 | 80 | |
| 2 | 2023 | 45 | |
| 3 | 2018 | 28 | |
| 4 | 2022 | 27 | |
| 5 | 2008 | 24 | |
| 6 | Hypoxia increases expression of CXC chemokine receptor 4 via activation of PI3K/Akt leading to enhanced migration of endothelial progenitor cells. | 2017 | 23 |
| 7 | 2011 | 18 | |
| 8 | 2021 | 16 | |
| 9 | 2015 | 15 | |
| 10 | 2018 | 13 | |
| 11 | 2018 | 13 | |
| 12 | 2024 | 13 | |
| 13 | 2017 | 12 | |
| 14 | 2022 | 12 | |
| 15 | 2018 | 11 | |
| 16 | 2020 | 11 | |
| 17 | 2017 | 10 | |
| 18 | 2022 | 10 | |
| 19 | 2020 | 9 | |
| 20 | 2020 | 6 |
About Tingjun Dai
Tingjun Dai is a scholar working on Epidemiology, Molecular Biology, Neurology, Rheumatology and Genetics, having authored 39 papers that have together received 427 indexed citations. Recurring topics across this work include Inflammatory Myopathies and Dermatomyositis (21 papers), Muscle Physiology and Disorders (10 papers), Eosinophilic Disorders and Syndromes (6 papers), Parkinson's Disease and Spinal Disorders (4 papers), Cardiomyopathy and Myosin Studies (4 papers), Parkinson's Disease Mechanisms and Treatments (3 papers), Skin Diseases and Diabetes (3 papers) and Genetic Neurodegenerative Diseases (3 papers). The work is most often cited by research in Clinical Biochemistry (82 citations), Neurology (75 citations), Epidemiology (152 citations), Cellular and Molecular Neuroscience (78 citations) and Genetics (41 citations). Tingjun Dai has collaborated with scholars based in China, Canada and United States. Frequent co-authors include Chuanzhu Yan, Ying Hou, Yuying Zhao, Pengfei Lin, Wei Li, Bing Wen, Haihong Zheng, Yanyan Zhao, H. Li and Junwei Wu. Their work appears in journals such as CNS Neuroscience & Therapeutics, Neurological Sciences, Arthritis Research & Therapy, Journal of Neuropathology & Experimental Neurology and Journal of Neurology.
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.