Chu‐Wei Kuo
Impact in
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- Galectins and Cancer Biology
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- Glycosylation and Glycoproteins Research
- Viral Infectious Diseases and Gene Expression in Insects
Papers in
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- Glycosylation and Glycoproteins Research 16
- Ubiquitin and proteasome pathways 4
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- Advanced Proteomics Techniques and Applications 5
- Mass Spectrometry Techniques and Applications 3
- Co-authors
- Kay‐Hooi Khoo (23 shared papers)Donald L. Jarvis (5 shared papers)Hideaki Mabashi‐Asazuma (3 shared papers)He‐Hsuan Hsiao (1 shared paper)I‐Lin Wu (1 shared paper)Ann M. Toth (1 shared paper)Shu‐Mei Liang (1 shared paper)Chi‐Ming Liang (1 shared paper)
- Journals
- PROTEOMICS (3 papers)Journal of Biotechnology (2 papers)Molecular & Cellular Proteomics (2 papers)ACS Chemical Biology (2 papers)Analytical and Bioanalytical Chemistry (1 paper)
- Partner nations
- TaiwanUnited StatesJapan
In The Last Decade
Chu‐Wei Kuo
26 papers receiving 519 citations
Peers
Comparison fields: 5 of 80
- Immunology 147
- Molecular Biology 391
- Biotechnology 40
- Spectroscopy 61
- Organic Chemistry 101
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 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 46 | |
| 2 | 2012 | 44 | |
| 3 | 2018 | 42 | |
| 4 | 1999 | 38 | |
| 5 | 2014 | 35 | |
| 6 | 2020 | 34 | |
| 7 | 2005 | 31 | |
| 8 | 2015 | 31 | |
| 9 | 2015 | 30 | |
| 10 | 2016 | 28 | |
| 11 | 2011 | 25 | |
| 12 | 2008 | 20 | |
| 13 | 2018 | 20 | |
| 14 | 2021 | 15 | |
| 15 | 2014 | 15 | |
| 16 | 2014 | 14 | |
| 17 | 2020 | 10 | |
| 18 | 2013 | 8 | |
| 19 | 2022 | 7 | |
| 20 | 2013 | 6 |
About Chu‐Wei Kuo
Chu‐Wei Kuo is a scholar working on Molecular Biology, Spectroscopy, Cell Biology, Immunology and Organic Chemistry, having authored 26 papers that have together received 522 indexed citations. Recurring topics across this work include Glycosylation and Glycoproteins Research (16 papers), Advanced Proteomics Techniques and Applications (5 papers), Carbohydrate Chemistry and Synthesis (4 papers), Ubiquitin and proteasome pathways (4 papers), Galectins and Cancer Biology (3 papers), Transgenic Plants and Applications (3 papers), Proteoglycans and glycosaminoglycans research (3 papers) and Mass Spectrometry Techniques and Applications (3 papers). The work is most often cited by research in Immunology (147 citations), Molecular Biology (391 citations), Biotechnology (40 citations), Spectroscopy (61 citations) and Organic Chemistry (101 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, Hideaki Mabashi‐Asazuma, He‐Hsuan Hsiao, I‐Lin Wu, Ann M. Toth, Shu‐Mei Liang, Chi‐Ming Liang, Koichi Kato and Hirokazu Yagi. Their work appears in journals such as PROTEOMICS, Journal of Biotechnology, Molecular & Cellular Proteomics, ACS Chemical Biology and Analytical and Bioanalytical Chemistry.
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.