Kai Yang
Impact in
- Cancer Research top 5%
- Cancer-related molecular mechanisms research
- MicroRNA in disease regulation
- Cancer, Lipids, and Metabolism
- Cancer, Hypoxia, and Metabolism
- Geriatrics and Gerontology top 5%
- Sirtuins and Resveratrol in Medicine
Papers in
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- Metabolomics and Mass Spectrometry Studies 13
- RNA modifications and cancer 12
- Epigenetics and DNA Methylation 9
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- Cancer-related molecular mechanisms research 10
- Cancer, Lipids, and Metabolism 7
- MicroRNA in disease regulation 6
- Co-authors
- Liping Xie (14 shared papers)Qiqi Mao (12 shared papers)Xiangyi Zheng (11 shared papers)Kang Li (16 shared papers)Yan Hou (12 shared papers)Jie Qin (4 shared papers)Yiwei Lin (7 shared papers)Yu Bai (2 shared papers)
- Journals
- Scientific Reports (4 papers)Metabolomics (4 papers)Frontiers in Immunology (3 papers)Medicine (3 papers)Journal of Cellular Biochemistry (2 papers)
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Kai Yang
119 papers receiving 2.1k citations
Peers
Comparison fields: 5 of 153
- Cancer Research 593
- Geriatrics and Gerontology 116
- Molecular Biology 1.0k
- Oncology 265
- Reproductive Medicine 78
Countries citing papers authored by Kai Yang
This map shows the geographic impact of Kai 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 Kai Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kai Yang more than expected).
Fields of papers citing papers by Kai Yang
This network shows the impact of papers produced by Kai 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 Kai Yang. The network helps show where Kai Yang may publish in the future.
Co-authors
The 25 scholars most cited alongside Kai 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 127 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2009 | 162 | |
| 2 | 2014 | 106 | |
| 3 | 2012 | 81 | |
| 4 | 2017 | 81 | |
| 5 | 2018 | 59 | |
| 6 | 2008 | 59 | |
| 7 | 2013 | 57 | |
| 8 | 2017 | 53 | |
| 9 | 2021 | 47 | |
| 10 | 2016 | 46 | |
| 11 | 2013 | 42 | |
| 12 | 2013 | 42 | |
| 13 | 2021 | 41 | |
| 14 | 2016 | 41 | |
| 15 | 2016 | 40 | |
| 16 | 2011 | 39 | |
| 17 | 2018 | 36 | |
| 18 | 2018 | 34 | |
| 19 | 2010 | 34 | |
| 20 | 2015 | 33 |
About Kai Yang
Kai Yang is a scholar working on Molecular Biology, Cancer Research, Pulmonary and Respiratory Medicine, Oncology and Surgery, having authored 127 papers that have together received 2.1k indexed citations. Recurring topics across this work include Metabolomics and Mass Spectrometry Studies (13 papers), RNA modifications and cancer (12 papers), Cancer-related molecular mechanisms research (10 papers), Epigenetics and DNA Methylation (9 papers), Ferroptosis and cancer prognosis (8 papers), Cancer, Lipids, and Metabolism (7 papers), Radiomics and Machine Learning in Medical Imaging (6 papers) and MicroRNA in disease regulation (6 papers). The work is most often cited by research in Cancer Research (593 citations), Geriatrics and Gerontology (116 citations), Molecular Biology (1.0k citations), Oncology (265 citations) and Reproductive Medicine (78 citations). Kai Yang has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Liping Xie, Qiqi Mao, Xiangyi Zheng, Kang Li, Yan Hou, Jie Qin, Yiwei Lin, Yu Bai, Huafeng Shen and Hongyu Xie. Their work appears in journals such as Scientific Reports, Metabolomics, Frontiers in Immunology, Medicine and Journal of Cellular Biochemistry.
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.