Jinzhou Yuan
- Molecular Biology
- Immunology top 10%
- Oncology
- Cancer Research top 10%
- Biomedical Engineering
- Co-authors
- Peter A. SimsHanna Mendes LevitinErin BushHaim H. BauDavid M. RaizenYim Ling ChengPeter A. SzaboMichelle Miron
- Topics
- Single-cell and spatial transcriptomics (10 papers)Micro and Nano Robotics (6 papers)Microfluidic and Bio-sensing Technologies (5 papers)
- Partner nations
- United StatesChinaCanada
In The Last Decade
Jinzhou Yuan
27 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 110
- Molecular Biology 673
- Immunology 402
- Oncology 218
- Cancer Research 211
- Biomedical Engineering 153
Countries citing papers authored by Jinzhou Yuan
This map shows the geographic impact of Jinzhou Yuan'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 Jinzhou Yuan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jinzhou Yuan more than expected).
Fields of papers citing papers by Jinzhou Yuan
This network shows the impact of papers produced by Jinzhou Yuan. 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 Jinzhou Yuan. The network helps show where Jinzhou Yuan may publish in the future.
Co-authorship network of co-authors of Jinzhou Yuan
This figure shows the co-authorship network connecting the top 25 collaborators of Jinzhou Yuan. A scholar is included among the top collaborators of Jinzhou Yuan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jinzhou Yuan. Jinzhou Yuan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 81 | |
| 4 | 31 | |
| 5 | 45 | |
| 6 | 15 | |
| 7 | 43 | |
| 8 | Single-cell transcriptomics of human T cells reveals tissue and activation signatures in health and diseasebreakdown → | 346 |
| 9 | 160 | |
| 10 | 34 | |
| 11 | 131 | |
| 12 | 127 | |
| 13 | 96 | |
| 14 | 23 | |
| 15 | 21 | |
| 16 | 32 | |
| 17 | REGRESSION EQUATIONS FOR ESTIMATING THE QUALITY OF MAXIMAL INSTEP KICK BY MALES AND FEMALES IN SOCCER | 5 |
| 18 | 7 | |
| 19 | The reliability and sensitivity of indices related to cardiovascular fitness evaluation | 5 |
| 20 | 8 |
About Jinzhou Yuan
Jinzhou Yuan is a scholar working on Aging, Condensed Matter Physics and Developmental Neuroscience, having authored 28 papers that have together received 1.3k indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (10 papers), Micro and Nano Robotics (6 papers) and Microfluidic and Bio-sensing Technologies (5 papers). The work is most often cited by research in Aging (71 citations), Developmental Neuroscience (141 citations) and Immunology (402 citations). Jinzhou Yuan has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Peter A. Sims, Hanna Mendes Levitin, Erin Bush, Haim H. Bau, David M. Raizen, Yim Ling Cheng, Peter A. Szabo, Michelle Miron, Mark E. Snyder and Donna L. Färber. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Communications and Nano Letters.
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.