Kuang‐Lei Tsai
Impact in
- Aging top 5%
- Structural Biology top 5%
Papers in
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- RNA Research and Splicing 10
- RNA and protein synthesis mechanisms 9
- Genomics and Chromatin Dynamics 8
- DNA Repair Mechanisms 7
- RNA modifications and cancer 6
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- Enzyme Structure and Function 3
- Co-authors
- Francisco J. Asturias (9 shared papers)Ronald Conaway (4 shared papers)Joan Conaway (4 shared papers)Chieri Tomomori‐Sato (3 shared papers)Shigeo Sato (3 shared papers)Chwan‐Deng Hsiao (4 shared papers)Todd O. Yeates (2 shared papers)Kenji Murakami (6 shared papers)
- Journals
- Molecular Cell (2 papers)Nucleic Acids Research (2 papers)Proceedings of the National Academy of Sciences (2 papers)Science Advances (2 papers)Journal of Biological Chemistry (2 papers)
- Partner nations
- United StatesTaiwanChina
In The Last Decade
Kuang‐Lei Tsai
25 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 81
- Aging 63
- Structural Biology 39
- Molecular Biology 1.3k
- Cell Biology 130
- Biomaterials 99
Countries citing papers authored by Kuang‐Lei Tsai
This map shows the geographic impact of Kuang‐Lei Tsai'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 Kuang‐Lei Tsai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kuang‐Lei Tsai more than expected).
Fields of papers citing papers by Kuang‐Lei Tsai
This network shows the impact of papers produced by Kuang‐Lei Tsai. 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 Kuang‐Lei Tsai. The network helps show where Kuang‐Lei Tsai may publish in the future.
Co-authors
The 25 scholars most cited alongside Kuang‐Lei Tsai, 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 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 258 | |
| 2 | 2014 | 176 | |
| 3 | 2013 | 175 | |
| 4 | 2007 | 166 | |
| 5 | 2017 | 112 | |
| 6 | 2011 | 95 | |
| 7 | 2015 | 82 | |
| 8 | 2013 | 82 | |
| 9 | 2021 | 66 | |
| 10 | 2006 | 60 | |
| 11 | 2014 | 59 | |
| 12 | 2008 | 58 | |
| 13 | 2021 | 45 | |
| 14 | 2018 | 36 | |
| 15 | 2022 | 25 | |
| 16 | 2016 | 22 | |
| 17 | 2021 | 17 | |
| 18 | 2009 | 17 | |
| 19 | 2023 | 16 | |
| 20 | 2021 | 8 |
About Kuang‐Lei Tsai
Kuang‐Lei Tsai is a scholar working on Molecular Biology, Materials Chemistry, Oncology, Cell Biology and Pathology and Forensic Medicine, having authored 25 papers that have together received 1.6k indexed citations. Recurring topics across this work include RNA Research and Splicing (10 papers), RNA and protein synthesis mechanisms (9 papers), Genomics and Chromatin Dynamics (8 papers), DNA Repair Mechanisms (7 papers), RNA modifications and cancer (6 papers), Microtubule and mitosis dynamics (3 papers), Cancer-related Molecular Pathways (3 papers) and Enzyme Structure and Function (3 papers). The work is most often cited by research in Aging (63 citations), Structural Biology (39 citations), Molecular Biology (1.3k citations), Cell Biology (130 citations) and Biomaterials (99 citations). Kuang‐Lei Tsai has collaborated with scholars based in United States, Taiwan and China. Frequent co-authors include Francisco J. Asturias, Ronald Conaway, Joan Conaway, Chieri Tomomori‐Sato, Shigeo Sato, Chwan‐Deng Hsiao, Todd O. Yeates, Kenji Murakami, John A. Tainer and Carol V. Robinson. Their work appears in journals such as Molecular Cell, Nucleic Acids Research, Proceedings of the National Academy of Sciences, Science Advances and Journal of Biological 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.