Kailu Yang
Impact in
- Structural Biology top 10%
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- SARS-CoV-2 and COVID-19 Research
- Tuberculosis Research and Epidemiology
Papers in
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- RNA and protein synthesis mechanisms 7
- RNA modifications and cancer 3
- Lipid Membrane Structure and Behavior 2
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- SARS-CoV-2 and COVID-19 Research 3
- Co-authors
- Junjie Zhang (8 shared papers)Axel T. Brünger (5 shared papers)Luis Esquivies (5 shared papers)James C. Sacchettini (2 shared papers)Richard A. Pfuetzner (4 shared papers)Jeng-Yih Chang (3 shared papers)Zhicheng Cui (3 shared papers)Ran Meng (2 shared papers)
- Journals
- Proceedings of the National Academy of Sciences (4 papers)Structure (2 papers)Nature (2 papers)Microbial Cell (1 paper)RNA (1 paper)
- Partner nations
- United StatesChinaGermany
In The Last Decade
Kailu Yang
23 papers receiving 392 citations
Peers
Comparison fields: 5 of 82
- Structural Biology 18
- Infectious Diseases 109
- Molecular Biology 242
- Aging 6
- Ecology 58
Countries citing papers authored by Kailu Yang
This map shows the geographic impact of Kailu Yang'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 Kailu Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kailu Yang more than expected).
Fields of papers citing papers by Kailu Yang
This network shows the impact of papers produced by Kailu Yang. 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 Kailu Yang. The network helps show where Kailu Yang may publish in the future.
Co-authors
The 25 scholars most cited alongside Kailu Yang, 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 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 55 | |
| 2 | 2022 | 50 | |
| 3 | 2015 | 43 | |
| 4 | 2019 | 36 | |
| 5 | 2022 | 35 | |
| 6 | 2022 | 27 | |
| 7 | 2024 | 23 | |
| 8 | 2016 | 23 | |
| 9 | 2014 | 21 | |
| 10 | 2021 | 21 | |
| 11 | 2015 | 15 | |
| 12 | 1994 | 9 | |
| 13 | 2023 | 7 | |
| 14 | 2020 | 6 | |
| 15 | 2022 | 6 | |
| 16 | 2022 | 4 | |
| 17 | 2021 | 4 | |
| 18 | [A study on C-erbB2, nm23 and p53 expressions in epithelial ovarian cancer and their clinical significance]. | 1999 | 2 |
| 19 | 2016 | 2 | |
| 20 | 2022 | 2 |
About Kailu Yang
Kailu Yang is a scholar working on Molecular Biology, Infectious Diseases, Atomic and Molecular Physics, and Optics, Electrical and Electronic Engineering and Ecology, having authored 24 papers that have together received 394 indexed citations. Recurring topics across this work include RNA and protein synthesis mechanisms (7 papers), Bacterial Genetics and Biotechnology (3 papers), SARS-CoV-2 and COVID-19 Research (3 papers), RNA modifications and cancer (3 papers), Photonic and Optical Devices (3 papers), Magnetism in coordination complexes (2 papers), Lipid Membrane Structure and Behavior (2 papers) and Bacteriophages and microbial interactions (2 papers). The work is most often cited by research in Structural Biology (18 citations), Infectious Diseases (109 citations), Molecular Biology (242 citations), Aging (6 citations) and Ecology (58 citations). Kailu Yang has collaborated with scholars based in United States, China and Germany. Frequent co-authors include Junjie Zhang, Axel T. Brünger, Luis Esquivies, James C. Sacchettini, Richard A. Pfuetzner, Jeng-Yih Chang, Zhicheng Cui, Ran Meng, Joanita Jakana and Chuchu Wang. Their work appears in journals such as Proceedings of the National Academy of Sciences, Structure, Nature, Microbial Cell and RNA.
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.