Chu‐Wei Kuo
Impact in
- Immunology top 10%
- Galectins and Cancer Biology
- Immunotherapy and Immune Responses
- Immune Cell Function and Interaction
- Oncology top 10%
- Cancer Immunotherapy and Biomarkers
- Cancer Cells and Metastasis
Papers in
-
- Glycosylation and Glycoproteins Research 16
- Ubiquitin and proteasome pathways 4
-
- Galectins and Cancer Biology 4
- Co-authors
- Kay‐Hooi Khoo (25 shared papers)Donald L. Jarvis (5 shared papers)Yi‐Hsin Elsa Hsu (1 shared paper)Shih-Shin Chang (1 shared paper)Jong‐Ho Cha (1 shared paper)Chun‐Te Chen (1 shared paper)Seung-Oe Lim (1 shared paper)Jung-Mao Hsu (1 shared paper)
- Journals
- PROTEOMICS (3 papers)ACS Chemical Biology (2 papers)Molecular & Cellular Proteomics (2 papers)Journal of Biotechnology (2 papers)Cancer Immunology Research (1 paper)
- Partner nations
- TaiwanUnited StatesJapan
In The Last Decade
Chu‐Wei Kuo
27 papers receiving 922 citations
Peers
Comparison fields: 5 of 86
- Immunology 299
- Oncology 257
- Molecular Biology 545
- Biotechnology 59
- Cancer Research 73
Countries citing papers authored by Chu‐Wei Kuo
This map shows the geographic impact of Chu‐Wei Kuo'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 Chu‐Wei Kuo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chu‐Wei Kuo more than expected).
Fields of papers citing papers by Chu‐Wei Kuo
This network shows the impact of papers produced by Chu‐Wei Kuo. 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 Chu‐Wei Kuo. The network helps show where Chu‐Wei Kuo may publish in the future.
Co-authors
The 25 scholars most cited alongside Chu‐Wei Kuo, 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 | 2018 | 359 | |
| 2 | 2021 | 53 | |
| 3 | 2012 | 47 | |
| 4 | 1999 | 46 | |
| 5 | 2018 | 43 | |
| 6 | 2014 | 37 | |
| 7 | 2015 | 37 | |
| 8 | 2020 | 35 | |
| 9 | 2015 | 32 | |
| 10 | 2005 | 31 | |
| 11 | 2016 | 30 | |
| 12 | 2011 | 28 | |
| 13 | 2008 | 24 | |
| 14 | 2018 | 21 | |
| 15 | 2021 | 16 | |
| 16 | 2014 | 15 | |
| 17 | 2014 | 15 | |
| 18 | 2020 | 10 | |
| 19 | 2024 | 10 | |
| 20 | 2013 | 8 |
About Chu‐Wei Kuo
Chu‐Wei Kuo is a scholar working on Molecular Biology, Immunology, Spectroscopy, Cell Biology and Organic Chemistry, having authored 27 papers that have together received 930 indexed citations. Recurring topics across this work include Glycosylation and Glycoproteins Research (16 papers), Advanced Proteomics Techniques and Applications (5 papers), Ubiquitin and proteasome pathways (4 papers), Galectins and Cancer Biology (4 papers), Carbohydrate Chemistry and Synthesis (4 papers), Transgenic Plants and Applications (3 papers), Monoclonal and Polyclonal Antibodies Research (3 papers) and Mass Spectrometry Techniques and Applications (3 papers). The work is most often cited by research in Immunology (299 citations), Oncology (257 citations), Molecular Biology (545 citations), Biotechnology (59 citations) and Cancer Research (73 citations). Chu‐Wei Kuo has collaborated with scholars based in Taiwan, United States and Japan. Frequent co-authors include Kay‐Hooi Khoo, Donald L. Jarvis, Yi‐Hsin Elsa Hsu, Shih-Shin Chang, Jong‐Ho Cha, Chun‐Te Chen, Seung-Oe Lim, Jung-Mao Hsu, Li-Chuan Chan and Mien‐Chie Hung. Their work appears in journals such as PROTEOMICS, ACS Chemical Biology, Molecular & Cellular Proteomics, Journal of Biotechnology and Cancer Immunology 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.