Chia-Yung Wu
About
In The Last Decade
Chia-Yung Wu
8 papers receiving 707 citations
Hit Papers
Peers
Comparison fields: 5 of 67
- Oncology 459
- Molecular Biology 350
- Biomedical Engineering 243
- Genetics 160
- Immunology 151
Countries citing papers authored by Chia-Yung Wu
This map shows the geographic impact of Chia-Yung 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 Chia-Yung Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chia-Yung Wu more than expected).
Fields of papers citing papers by Chia-Yung Wu
This network shows the impact of papers produced by Chia-Yung 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 Chia-Yung Wu. The network helps show where Chia-Yung Wu may publish in the future.
Co-authorship network of co-authors of Chia-Yung Wu
This figure shows the co-authorship network connecting the top 25 collaborators of Chia-Yung Wu. A scholar is included among the top collaborators of Chia-Yung Wu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Chia-Yung Wu. Chia-Yung Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | 10 | |
| 3 | 39 | |
| 4 | Remote control of therapeutic T cells through a small molecule–gated chimeric receptor breakdown → | 552 |
| 5 | 25 | |
| 6 | 17 | |
| 7 | 57 | |
| 8 | 7 |
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.