Te-Chia Wu
Impact in
- Immunology top 10%
- Immune Cell Function and Interaction
- Immunotherapy and Immune Responses
- Immune cells in cancer
- T-cell and B-cell Immunology
- IL-33, ST2, and ILC Pathways
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- Cancer Immunotherapy and Biomarkers
Papers in
-
- Immunotherapy and Immune Responses 6
- Immune cells in cancer 3
- Immune Cell Function and Interaction 3
- Oncology 7
- Cancer Immunotherapy and Biomarkers 5
- CAR-T cell therapy research 2
- Co-authors
- Karolina Palucka (11 shared papers)Jacques Banchereau (6 shared papers)Florentina Marches (7 shared papers)Alexander Pedroza‐González (2 shared papers)Yong‐Jun Liu (2 shared papers)Kangling Xu (2 shared papers)Joshy George (4 shared papers)Jan Martínek (9 shared papers)
- Journals
- The Journal of Experimental Medicine (3 papers)Cancer Research (1 paper)Cancer Immunology Research (1 paper)American Journal of Physiology-Lung Cellular and Molecular Physiology (1 paper)Methods in enzymology on CD-ROM/Methods in enzymology (1 paper)
- Partner nations
- United StatesRussiaJapan
In The Last Decade
Te-Chia Wu
13 papers receiving 697 citations
Peers
Comparison fields: 5 of 70
- Immunology 373
- Oncology 218
- Immunology and Allergy 49
- Dermatology 70
- Biological Psychiatry 12
Countries citing papers authored by Te-Chia Wu
This map shows the geographic impact of Te-Chia Wu'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 Te-Chia Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Te-Chia Wu more than expected).
Fields of papers citing papers by Te-Chia Wu
This network shows the impact of papers produced by Te-Chia Wu. 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 Te-Chia Wu. The network helps show where Te-Chia Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Te-Chia Wu, 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 | 2011 | 206 | |
| 2 | 2017 | 156 | |
| 3 | 2018 | 135 | |
| 4 | 2014 | 69 | |
| 5 | 2007 | 48 | |
| 6 | 2019 | 37 | |
| 7 | 2022 | 23 | |
| 8 | 2022 | 9 | |
| 9 | 2023 | 7 | |
| 10 | 2021 | 6 | |
| 11 | 2023 | 6 | |
| 12 | 2019 | 4 | |
| 13 | 2022 | 1 | |
| 14 | 2026 | 0 |
About Te-Chia Wu
Te-Chia Wu is a scholar working on Immunology, Oncology, Infectious Diseases, Immunology and Allergy and Biotechnology, having authored 14 papers that have together received 707 indexed citations. Recurring topics across this work include Immunotherapy and Immune Responses (6 papers), Cancer Immunotherapy and Biomarkers (5 papers), Immune cells in cancer (3 papers), Immune Cell Function and Interaction (3 papers), Viral gastroenteritis research and epidemiology (2 papers), CAR-T cell therapy research (2 papers), Neonatal Respiratory Health Research (2 papers) and Respiratory Support and Mechanisms (2 papers). The work is most often cited by research in Immunology (373 citations), Oncology (218 citations), Immunology and Allergy (49 citations), Dermatology (70 citations) and Biological Psychiatry (12 citations). Te-Chia Wu has collaborated with scholars based in United States, Russia and Japan. Frequent co-authors include Karolina Palucka, Jacques Banchereau, Florentina Marches, Alexander Pedroza‐González, Yong‐Jun Liu, Kangling Xu, Joshy George, Jan Martínek, Cheng‐Han Chung and George A. Kuchel. Their work appears in journals such as The Journal of Experimental Medicine, Cancer Research, Cancer Immunology Research, American Journal of Physiology-Lung Cellular and Molecular Physiology and Methods in enzymology on CD-ROM/Methods in enzymology.
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.