Kaige Yan
Impact in
- Structural Biology top 5%
- Molecular Biology top 10%
- RNA and protein synthesis mechanisms
- RNA modifications and cancer
- Mitochondrial Function and Pathology
- RNA Research and Splicing
- ATP Synthase and ATPases Research
- Photosynthetic Processes and Mechanisms
- Genomics and Chromatin Dynamics
Papers in
-
- RNA modifications and cancer 10
- RNA and protein synthesis mechanisms 8
- RNA Research and Splicing 3
- Genomics and Chromatin Dynamics 3
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- Microtubule and mitosis dynamics 3
- Co-authors
- Ning Gao (10 shared papers)Jianlin Lei (6 shared papers)Maojun Yang (1 shared paper)Meng Wu (1 shared paper)Runyu Guo (1 shared paper)Jinke Gu (1 shared paper)Zhifei Li (4 shared papers)Chengying Ma (4 shared papers)
- Journals
- Nature Communications (4 papers)Nature Structural & Molecular Biology (3 papers)Nature (3 papers)Protein & Cell (2 papers)Nature Plants (2 papers)
- Partner nations
- ChinaUnited KingdomUnited States
In The Last Decade
Kaige Yan
23 papers receiving 948 citations
Peers
Comparison fields: 5 of 77
- Structural Biology 34
- Molecular Biology 841
- Clinical Biochemistry 53
- Cell Biology 94
- Genetics 95
Countries citing papers authored by Kaige Yan
This map shows the geographic impact of Kaige Yan'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 Kaige Yan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kaige Yan more than expected).
Fields of papers citing papers by Kaige Yan
This network shows the impact of papers produced by Kaige Yan. 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 Kaige Yan. The network helps show where Kaige Yan may publish in the future.
Co-authors
The 25 scholars most cited alongside Kaige Yan, 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 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 272 | |
| 2 | 2016 | 170 | |
| 3 | 2019 | 99 | |
| 4 | 2017 | 79 | |
| 5 | 2015 | 67 | |
| 6 | 2014 | 38 | |
| 7 | 2020 | 32 | |
| 8 | 2023 | 26 | |
| 9 | 2023 | 23 | |
| 10 | 2014 | 22 | |
| 11 | 2018 | 19 | |
| 12 | 2016 | 18 | |
| 13 | 2021 | 16 | |
| 14 | 2022 | 14 | |
| 15 | 2015 | 13 | |
| 16 | 2024 | 11 | |
| 17 | 2023 | 9 | |
| 18 | 2016 | 9 | |
| 19 | 2023 | 4 | |
| 20 | 2016 | 4 |
About Kaige Yan
Kaige Yan is a scholar working on Molecular Biology, Cell Biology, Plant Science, Oncology and Genetics, having authored 23 papers that have together received 952 indexed citations. Recurring topics across this work include RNA modifications and cancer (10 papers), RNA and protein synthesis mechanisms (8 papers), Microtubule and mitosis dynamics (3 papers), RNA Research and Splicing (3 papers), Chromosomal and Genetic Variations (3 papers), Genomics and Chromatin Dynamics (3 papers), Plant Molecular Biology Research (2 papers) and Peptidase Inhibition and Analysis (2 papers). The work is most often cited by research in Structural Biology (34 citations), Molecular Biology (841 citations), Clinical Biochemistry (53 citations), Cell Biology (94 citations) and Genetics (95 citations). Kaige Yan has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Ning Gao, Jianlin Lei, Maojun Yang, Meng Wu, Runyu Guo, Jinke Gu, Zhifei Li, Chengying Ma, Shan Wu and John L. Woolford. Their work appears in journals such as Nature Communications, Nature Structural & Molecular Biology, Nature, Protein & Cell and Nature Plants.
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.