Chia‐Yi Kuan
- Molecular Biology top 1%
- Cellular and Molecular Neuroscience top 1%
- Cell Biology top 1%
- Immunology top 5%
- Oncology top 5%
- Co-authors
- Richard A. FlavellPasko RakićHajime KarasuyamaKeisuke KuidaTimothy S. ZhengRoger J. DavisDerek YangDi Yang
- Topics
- Cell death mechanisms and regulation (8 papers)Wnt/β-catenin signaling in development and cancer (4 papers)Melanoma and MAPK Pathways (3 papers)
- Partner nations
- United StatesJapanRussia
In The Last Decade
Chia‐Yi Kuan
21 papers receiving 5.6k citations
Hit Papers
Peers
Comparison fields: 5 of 118
- Molecular Biology 4.4k
- Cellular and Molecular Neuroscience 1.2k
- Cell Biology 789
- Immunology 786
- Oncology 717
Countries citing papers authored by Chia‐Yi Kuan
This map shows the geographic impact of Chia‐Yi Kuan'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‐Yi Kuan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chia‐Yi Kuan more than expected).
Fields of papers citing papers by Chia‐Yi Kuan
This network shows the impact of papers produced by Chia‐Yi Kuan. 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‐Yi Kuan. The network helps show where Chia‐Yi Kuan may publish in the future.
Co-authorship network of co-authors of Chia‐Yi Kuan
This figure shows the co-authorship network connecting the top 25 collaborators of Chia‐Yi Kuan. A scholar is included among the top collaborators of Chia‐Yi Kuan 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‐Yi Kuan. Chia‐Yi Kuan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 24 | |
| 3 | 13 | |
| 4 | 5 | |
| 5 | 130 | |
| 6 | 97 | |
| 7 | 3 | |
| 8 | 58 | |
| 9 | 67 | |
| 10 | Promiscuous recombination of LoxP alleles during gametogenesis in cornea Cre driver mice. | 15 |
| 11 | 92 | |
| 12 | 104 | |
| 13 | 77 | |
| 14 | 49 | |
| 15 | 70 | |
| 16 | 12 | |
| 17 | The Jnk1 and Jnk2 Protein Kinases Are Required for Regional Specific Apoptosis during Early Brain Developmentbreakdown → | 750 |
| 18 | Reduced Apoptosis and Cytochrome c–Mediated Caspase Activation in Mice Lacking Caspase 9breakdown → | 1369 |
| 19 | Absence of excitotoxicity-induced apoptosis in the hippocampus of mice lacking the Jnk3 genebreakdown → | 1070 |
| 20 | Decreased apoptosis in the brain and premature lethality in CPP32-deficient micebreakdown → | 1613 |
About Chia‐Yi Kuan
Chia‐Yi Kuan is a scholar working on Developmental Neuroscience, Cell Biology and Neurology, having authored 21 papers that have together received 5.7k indexed citations. Recurring topics across this work include Cell death mechanisms and regulation (8 papers), Wnt/β-catenin signaling in development and cancer (4 papers) and Melanoma and MAPK Pathways (3 papers). The work is most often cited by research in Developmental Neuroscience (511 citations), Cellular and Molecular Neuroscience (1.2k citations) and Molecular Biology (4.4k citations). Chia‐Yi Kuan has collaborated with scholars based in United States, Japan and Russia. Frequent co-authors include Richard A. Flavell, Pasko Rakić, Hajime Karasuyama, Keisuke Kuida, Timothy S. Zheng, Roger J. Davis, Derek Yang, Di Yang, Songqing Na and Choji Taya. Their work appears in journals such as Nature, Cell and Proceedings of the National Academy of Sciences.
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.