Yusha Sun
Impact in
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- Cancer Cells and Metastasis
- CAR-T cell therapy research
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- Cancer Genomics and Diagnostics
Papers in
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- Single-cell and spatial transcriptomics 2
- Oncology 6
- CAR-T cell therapy research 3
- Co-authors
- Robert H. Austin (7 shared papers)Thomas Werner (3 shared papers)Abass Alavi (3 shared papers)Kenneth J. Pienta (7 shared papers)William Raynor (3 shared papers)Peter Sang Uk Park (3 shared papers)Gonzalo Torga (5 shared papers)James C. Sturm (4 shared papers)
- Journals
- Neuro-Oncology (3 papers)Cell stem cell (2 papers)Journal of Visualized Experiments (2 papers)Nature Protocols (1 paper)Blood (1 paper)
- Partner nations
- United StatesChinaDenmark
In The Last Decade
Yusha Sun
25 papers receiving 282 citations
Peers
Comparison fields: 5 of 60
- Oncology 74
- Cancer Research 39
- Genetics 26
- Food Science 36
- Cell Biology 31
Countries citing papers authored by Yusha Sun
This map shows the geographic impact of Yusha Sun'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 Yusha Sun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yusha Sun more than expected).
Fields of papers citing papers by Yusha Sun
This network shows the impact of papers produced by Yusha Sun. 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 Yusha Sun. The network helps show where Yusha Sun may publish in the future.
Co-authors
The 25 scholars most cited alongside Yusha Sun, 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 29 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 58 | |
| 2 | 2024 | 47 | |
| 3 | 2021 | 44 | |
| 4 | 2023 | 22 | |
| 5 | 2023 | 17 | |
| 6 | 2021 | 15 | |
| 7 | 2020 | 11 | |
| 8 | 2024 | 11 | |
| 9 | 2023 | 10 | |
| 10 | 2024 | 8 | |
| 11 | 2025 | 7 | |
| 12 | 2020 | 7 | |
| 13 | 2024 | 7 | |
| 14 | 2022 | 7 | |
| 15 | 2019 | 3 | |
| 16 | 2020 | 2 | |
| 17 | 2019 | 2 | |
| 18 | 2026 | 1 | |
| 19 | 2022 | 1 | |
| 20 | 2023 | 1 |
About Yusha Sun
Yusha Sun is a scholar working on Molecular Biology, Oncology, Biomedical Engineering, Food Science and Genetics, having authored 29 papers that have together received 286 indexed citations. Recurring topics across this work include 3D Printing in Biomedical Research (4 papers), Proteins in Food Systems (4 papers), Mathematical Biology Tumor Growth (3 papers), CAR-T cell therapy research (3 papers), Glioma Diagnosis and Treatment (3 papers), Microfluidic and Bio-sensing Technologies (2 papers), Medical Imaging Techniques and Applications (2 papers) and Single-cell and spatial transcriptomics (2 papers). The work is most often cited by research in Oncology (74 citations), Cancer Research (39 citations), Genetics (26 citations), Food Science (36 citations) and Cell Biology (31 citations). Yusha Sun has collaborated with scholars based in United States, China and Denmark. Frequent co-authors include Robert H. Austin, Thomas Werner, Abass Alavi, Kenneth J. Pienta, William Raynor, Peter Sang Uk Park, Gonzalo Torga, James C. Sturm, Robert Axelrod and Hongjun Song. Their work appears in journals such as Neuro-Oncology, Cell stem cell, Journal of Visualized Experiments, Nature Protocols and Blood.
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.