Yan Xing
Impact in
- Immunology top 2%
- Immune Cell Function and Interaction
- T-cell and B-cell Immunology
- Immunotherapy and Immune Responses
- Immune Response and Inflammation
- IL-33, ST2, and ILC Pathways
- Oncology top 10%
- CAR-T cell therapy research
Papers in
- Immunology 15
- Immune Cell Function and Interaction 7
- T-cell and B-cell Immunology 7
- Immunotherapy and Immune Responses 5
- Reproductive System and Pregnancy 2
- Genetics 6
- Chronic Lymphocytic Leukemia Research 4
- Co-authors
- Kristin A. HogquistAmy E. MoranJennifer A. PuntJonathan S. MaltzmanNicole R. CunninghamXiaodan WangStephen C. JamesonNobuo Sakaguchi
- Journals
- The Journal of Immunology (3 papers)Nature Immunology (3 papers)The Journal of Experimental Medicine (2 papers)Cancer Research (2 papers)Molecular Cancer Therapeutics (1 paper)
- Partner nations
- ChinaUnited StatesJapan
In The Last Decade
Yan Xing
30 papers receiving 1.7k citations
Hit Papers
Peers
Comparison fields: 5 of 83
- Immunology 1.2k
- Oncology 346
- Genetics 106
- Hematology 102
- Molecular Biology 381
Countries citing papers authored by Yan Xing
This map shows the geographic impact of Yan Xing'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 Xing with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yan Xing more than expected).
Fields of papers citing papers by Yan Xing
This network shows the impact of papers produced by Yan Xing. 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 Xing. The network helps show where Yan Xing may publish in the future.
Co-authors
The 25 scholars most cited alongside Yan Xing, 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 | 0 | |
| 2 | 2025 | 1 | |
| 3 | 2025 | 0 | |
| 4 | 2023 | 11 | |
| 5 | 2021 | 36 | |
| 6 | 2021 | 68 | |
| 7 | 2020 | 58 | |
| 8 | 2020 | 1 | |
| 9 | 2018 | 7 | |
| 10 | 2017 | 22 | |
| 11 | 2016 | 15 | |
| 12 | 2016 | 1 | |
| 13 | 2014 | 13 | |
| 14 | 2014 | 215 | |
| 15 | 2013 | 6 | |
| 16 | 2012 | 5 | |
| 17 | T cell receptor signal strength in Treg and iNKT cell development demonstrated by a novel fluorescent reporter mouse Hit paper breakdown → | 2011 | 769 |
| 18 | 2009 | 35 | |
| 19 | 2007 | 13 | |
| 20 | 2005 | 38 |
About Yan Xing
Yan Xing is a scholar working on Immunology, Genetics, Hematology, Cancer Research and Pathology and Forensic Medicine, having authored 32 papers that have together received 1.7k indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (7 papers), T-cell and B-cell Immunology (7 papers), Immunotherapy and Immune Responses (5 papers), Chronic Lymphocytic Leukemia Research (4 papers), Acute Myeloid Leukemia Research (4 papers), PI3K/AKT/mTOR signaling in cancer (3 papers), Autoimmune Bullous Skin Diseases (2 papers) and Reproductive System and Pregnancy (2 papers). The work is most often cited by research in Immunology (1.2k citations), Oncology (346 citations), Genetics (106 citations), Hematology (102 citations) and Molecular Biology (381 citations). Yan Xing has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Kristin A. Hogquist, Amy E. Moran, Jennifer A. Punt, Jonathan S. Maltzman, Nicole R. Cunningham, Xiaodan Wang, Stephen C. Jameson, Nobuo Sakaguchi, Jason M. Schenkel and David L. Owen. Their work appears in journals such as The Journal of Immunology, Nature Immunology, The Journal of Experimental Medicine, Cancer Research and Molecular Cancer Therapeutics.
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.