Xin Niu
- Cancer Research top 1%
- MicroRNA in disease regulation 9
- Genetics top 2%
- Mesenchymal stem cell research 8
- Urology top 2%
- Molecular Biology top 5%
- Extracellular vesicles in disease 20
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- Advanced Neural Network Applications 13
- Advanced Image and Video Retrieval Techniques 7
- Face and Expression Recognition 5
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- Domain Adaptation and Few-Shot Learning 8
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- Tissue Engineering and Regenerative Medicine 6
- Co-authors
- Qing LiYang WangBin HuJieyuan ZhangBizeng ZhaoChun‐Yuan ChenHaiyan LiYunlong Yang
- Cited by
- Cancer ResearchGeneticsUrology
- Journals
- Advanced Materials (1 paper)SHILAP Revista de lepidopterología (2 papers)PLoS ONE (1 paper)
- Partner nations
- ChinaAustraliaUnited States
In The Last Decade
Xin Niu
79 papers receiving 4.0k citations
Hit Papers
Peers
Comparison fields: 5 of 156
- Cancer Research 1.3k
- Genetics 598
- Urology 231
- Molecular Biology 2.4k
- Orthopedics and Sports Medicine 280
Countries citing papers authored by Xin Niu
This map shows the geographic impact of Xin Niu'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 Xin Niu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xin Niu more than expected).
Fields of papers citing papers by Xin Niu
This network shows the impact of papers produced by Xin Niu. 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 Xin Niu. The network helps show where Xin Niu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Xin Niu, 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 | 1 | |
| 2 | 2025 | 3 | |
| 3 | 2024 | 13 | |
| 4 | 2024 | 0 | |
| 5 | 2024 | 3 | |
| 6 | 2023 | 0 | |
| 7 | 2022 | 67 | |
| 8 | 2022 | 75 | |
| 9 | 2022 | 8 | |
| 10 | 2021 | 44 | |
| 11 | 2018 | 57 | |
| 12 | 2018 | 25 | |
| 13 | 2017 | 208 | |
| 14 | 2017 | 58 | |
| 15 | 2017 | 25 | |
| 16 | 2016 | 137 | |
| 17 | 2015 | 26 | |
| 18 | Clinical trial and assessment of a portable apparatus for auxiliary diagnosis and treatment based on four TCM diagnostic methods | 2011 | 1 |
| 19 | 2011 | 34 | |
| 20 | 2008 | 73 |
About Xin Niu
Xin Niu is a scholar working on Computer Vision and Pattern Recognition, Genetics and Process Chemistry and Technology, having authored 87 papers that have together received 4.0k indexed citations. Recurring topics across this work include Extracellular vesicles in disease (20 papers), Advanced Neural Network Applications (13 papers), MicroRNA in disease regulation (9 papers), Domain Adaptation and Few-Shot Learning (8 papers), Mesenchymal stem cell research (8 papers), Advanced Image and Video Retrieval Techniques (7 papers), Tissue Engineering and Regenerative Medicine (6 papers) and Face and Expression Recognition (5 papers). The work is most often cited by research in Cancer Research (1.3k citations), Genetics (598 citations) and Urology (231 citations). Xin Niu has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Qing Li, Yang Wang, Bin Hu, Jieyuan Zhang, Yang Wang, Bizeng Zhao, Chun‐Yuan Chen, Haiyan Li, Yunlong Yang and Changqing Zhang. Their work appears in journals such as Advanced Materials, SHILAP Revista de lepidopterología and PLoS ONE.
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.