Dan Chen
Impact in
- Cancer Research top 10%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Hematology top 10%
Papers in
-
- Circular RNAs in diseases 3
- Oncology 15
- CAR-T cell therapy research 4
- Co-authors
- Gangli An (3 shared papers)Huimin Meng (3 shared papers)Fengtao You (3 shared papers)Licui Jiang (3 shared papers)Lin Yang (3 shared papers)Bowen Li (1 shared paper)Xinyue Dong (1 shared paper)Haiyan Chen (1 shared paper)
- Journals
- Blood (3 papers)Frontiers in Immunology (2 papers)Chemico-Biological Interactions (2 papers)American Journal of Cancer Research (1 paper)Parasitology Research (1 paper)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Dan Chen
52 papers receiving 992 citations
Peers
Comparison fields: 5 of 97
- Cancer Research 184
- Hematology 122
- Oncology 268
- Immunology 206
- Rheumatology 113
Countries citing papers authored by Dan Chen
This map shows the geographic impact of Dan Chen'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 Dan Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dan Chen more than expected).
Fields of papers citing papers by Dan Chen
This network shows the impact of papers produced by Dan Chen. 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 Dan Chen. The network helps show where Dan Chen may publish in the future.
Co-authors
The 25 scholars most cited alongside Dan Chen, 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 56 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | A novel CD7 chimeric antigen receptor-modified NK-92MI cell line targeting T-cell acute lymphoblastic leukemia. | 2019 | 116 |
| 2 | 2017 | 91 | |
| 3 | 2015 | 90 | |
| 4 | 2021 | 46 | |
| 5 | 2015 | 45 | |
| 6 | 2015 | 44 | |
| 7 | 2013 | 44 | |
| 8 | 2019 | 36 | |
| 9 | 2017 | 34 | |
| 10 | 2016 | 33 | |
| 11 | 2017 | 29 | |
| 12 | 2015 | 29 | |
| 13 | 2022 | 29 | |
| 14 | 2022 | 26 | |
| 15 | MUC1-Tn-targeting chimeric antigen receptor-modified Vγ9Vδ2 T cells with enhanced antigen-specific anti-tumor activity. | 2021 | 25 |
| 16 | 2014 | 23 | |
| 17 | 2011 | 22 | |
| 18 | 2015 | 22 | |
| 19 | Red blood cell distribution width: a potential maker estimating disease activity of ankylosing spondylitis. | 2014 | 22 |
| 20 | 2019 | 16 |
About Dan Chen
Dan Chen is a scholar working on Molecular Biology, Oncology, Hematology, Immunology and Rheumatology, having authored 56 papers that have together received 1.0k indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (6 papers), MicroRNA in disease regulation (6 papers), Bone and Joint Diseases (5 papers), Immunotherapy and Immune Responses (4 papers), CAR-T cell therapy research (4 papers), Platelet Disorders and Treatments (4 papers), T-cell and B-cell Immunology (3 papers) and Circular RNAs in diseases (3 papers). The work is most often cited by research in Cancer Research (184 citations), Hematology (122 citations), Oncology (268 citations), Immunology (206 citations) and Rheumatology (113 citations). Dan Chen has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Gangli An, Huimin Meng, Fengtao You, Licui Jiang, Lin Yang, Bowen Li, Xinyue Dong, Haiyan Chen, Xuejun Zhu and Yinyan Wang. Their work appears in journals such as Blood, Frontiers in Immunology, Chemico-Biological Interactions, American Journal of Cancer Research and Parasitology Research.
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.