Yan Dou
- Biomaterials top 5%
- Nanoparticle-Based Drug Delivery 6
- Cancer Research top 10%
- Biomedical Engineering top 5%
- Nanoplatforms for cancer theranostics 11
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- Alzheimer's disease research and treatments 8
- Biochemical effects in animals 3
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- Neuroinflammation and Neurodegeneration Mechanisms 7
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- Image and Object Detection Techniques 4
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- Lung Cancer Research Studies 4
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- Advanced Nanomaterials in Catalysis 3
- Partner nations
- ChinaUnited StatesTaiwan
In The Last Decade
Yan Dou
77 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 140
- Biomaterials 260
- Cancer Research 199
- Biomedical Engineering 558
- Biological Psychiatry 18
- Pulmonary and Respiratory Medicine 233
Countries citing papers authored by Yan Dou
This map shows the geographic impact of Yan Dou'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 Yan Dou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yan Dou more than expected).
Fields of papers citing papers by Yan Dou
This network shows the impact of papers produced by Yan Dou. 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 Yan Dou. The network helps show where Yan Dou may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Yan Dou, 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 | 2025 | 2 | |
| 2 | 2024 | 4 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 0 | |
| 5 | 2024 | 3 | |
| 6 | 2024 | 0 | |
| 7 | 2023 | 4 | |
| 8 | 2023 | 0 | |
| 9 | 2023 | 0 | |
| 10 | 2023 | 8 | |
| 11 | 2020 | 4 | |
| 12 | 2020 | 4 | |
| 13 | 2018 | 174 | |
| 14 | 2018 | 72 | |
| 15 | Application of high-throughput sequencing for analyzing bacterial communities in earthen ponds of sea cucumber aquaculture in northern China. | 2016 | 1 |
| 16 | Alternative Splicing and Expression Pattern Analyses of Two MADSBOX Genes AGL6 and FUL1 in Brachypodium distachyon | 2015 | 2 |
| 17 | 2014 | 8 | |
| 18 | 2011 | 13 | |
| 19 | 2011 | 25 | |
| 20 | Study on model and precision in spatial point detection based on different camera assignment | 2007 | 1 |
About Yan Dou
Yan Dou is a scholar working on Biological Psychiatry, Neurology and Endocrinology, having authored 85 papers that have together received 1.4k indexed citations. Recurring topics across this work include Nanoplatforms for cancer theranostics (11 papers), Alzheimer's disease research and treatments (8 papers), Neuroinflammation and Neurodegeneration Mechanisms (7 papers), Nanoparticle-Based Drug Delivery (6 papers), Image and Object Detection Techniques (4 papers), Lung Cancer Research Studies (4 papers), Advanced Nanomaterials in Catalysis (3 papers) and Biochemical effects in animals (3 papers). The work is most often cited by research in Biomaterials (260 citations), Cancer Research (199 citations) and Biomedical Engineering (558 citations). Yan Dou has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include Jin Chang, Xue Li, Yanyan Guo, Hanjie Wang, Xuening Zhang, Sheng Wang, Xiaoqun Gong, Menglin Wu, Lin Wang and Xiaodong Li. Their work appears in journals such as ACS Nano, ACS Applied Materials & Interfaces, Nano Today, Chemical Engineering Journal and Theranostics.
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.