Qiangda Chen
Impact in
- Physiology top 10%
- Adenosine and Purinergic Signaling
- Oncology top 10%
- Pancreatic and Hepatic Oncology Research
- Cancer Immunotherapy and Biomarkers
Papers in
- Oncology 18
- Pancreatic and Hepatic Oncology Research 12
- Cancer Immunotherapy and Biomarkers 5
- CAR-T cell therapy research 2
- Immunology 10
- Immune Cell Function and Interaction 4
- Immune cells in cancer 4
- Immunotherapy and Immune Responses 2
- Co-authors
- Ning Pu (25 shared papers)Hanlin Yin (22 shared papers)Wenchuan Wu (15 shared papers)Wenhui Lou (10 shared papers)Guochao Zhao (6 shared papers)Wenhui Lou (9 shared papers)Siyao Liu (5 shared papers)Dansong Wang (4 shared papers)
- Journals
- Advanced Science (2 papers)Critical Reviews in Oncology/Hematology (2 papers)International Journal of Surgery (2 papers)Journal for ImmunoTherapy of Cancer (2 papers)Annals of Translational Medicine (2 papers)
- Partner nations
- ChinaUnited StatesJapan
In The Last Decade
Qiangda Chen
27 papers receiving 464 citations
Peers
Comparison fields: 5 of 64
- Physiology 46
- Oncology 220
- Immunology 155
- Cancer Research 44
- Biotechnology 20
Countries citing papers authored by Qiangda Chen
This map shows the geographic impact of Qiangda 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 Qiangda Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qiangda Chen more than expected).
Fields of papers citing papers by Qiangda Chen
This network shows the impact of papers produced by Qiangda 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 Qiangda Chen. The network helps show where Qiangda Chen may publish in the future.
Co-authors
The 25 scholars most cited alongside Qiangda 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 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 68 | |
| 2 | 2020 | 63 | |
| 3 | 2023 | 59 | |
| 4 | 2022 | 48 | |
| 5 | 2020 | 34 | |
| 6 | 2019 | 28 | |
| 7 | 2023 | 18 | |
| 8 | 2022 | 16 | |
| 9 | 2020 | 12 | |
| 10 | 2021 | 12 | |
| 11 | 2021 | 11 | |
| 12 | 2021 | 11 | |
| 13 | 2023 | 11 | |
| 14 | 2023 | 11 | |
| 15 | 2022 | 10 | |
| 16 | 2021 | 10 | |
| 17 | 2024 | 9 | |
| 18 | 2021 | 7 | |
| 19 | 2021 | 7 | |
| 20 | 2022 | 6 |
About Qiangda Chen
Qiangda Chen is a scholar working on Oncology, Immunology, Surgery, Physiology and Cancer Research, having authored 27 papers that have together received 466 indexed citations. Recurring topics across this work include Pancreatic and Hepatic Oncology Research (12 papers), Cancer Immunotherapy and Biomarkers (5 papers), Immune Cell Function and Interaction (4 papers), Immune cells in cancer (4 papers), Adenosine and Purinergic Signaling (3 papers), CAR-T cell therapy research (2 papers), SARS-CoV-2 and COVID-19 Research (2 papers) and Immunotherapy and Immune Responses (2 papers). The work is most often cited by research in Physiology (46 citations), Oncology (220 citations), Immunology (155 citations), Cancer Research (44 citations) and Biotechnology (20 citations). Qiangda Chen has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Ning Pu, Hanlin Yin, Wenchuan Wu, Wenhui Lou, Guochao Zhao, Wenhui Lou, Siyao Liu, Dansong Wang, Jun Yu and Tiantao Kuang. Their work appears in journals such as Advanced Science, Critical Reviews in Oncology/Hematology, International Journal of Surgery, Journal for ImmunoTherapy of Cancer and Annals of Translational Medicine.
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.