Bei Guo
Impact in
- Cancer Research top 10%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Nephrology top 5%
Papers in
-
- Extracellular vesicles in disease 14
- RNA modifications and cancer 4
- Circular RNAs in diseases 3
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- MicroRNA in disease regulation 10
- Co-authors
- Ling‐Qing Yuan (27 shared papers)Su‐Kang Shan (26 shared papers)Fu‐Xing‐Zi Li (21 shared papers)Ming-Hui Zheng (22 shared papers)Xiao Lin (24 shared papers)Feng Xu (20 shared papers)Feng Wu (15 shared papers)Jia‐Yu Zhong (10 shared papers)
- Journals
- Frontiers in Endocrinology (7 papers)Frontiers in Cell and Developmental Biology (5 papers)Journal of Nanobiotechnology (4 papers)Cell Death and Disease (2 papers)Obesity Reviews (1 paper)
- Partner nations
- ChinaUnited StatesTaiwan
In The Last Decade
Bei Guo
35 papers receiving 1.1k citations
Bei Guo's Hit Papers
Peers
Comparison fields: 5 of 97
- Cancer Research 275
- Nephrology 114
- Molecular Biology 626
- Aging 13
- Genetics 71
Countries citing papers authored by Bei Guo
This map shows the geographic impact of Bei Guo'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 Bei Guo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bei Guo more than expected).
Fields of papers citing papers by Bei Guo
This network shows the impact of papers produced by Bei Guo. 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 Bei Guo. The network helps show where Bei Guo may publish in the future.
Co-authors
The 25 scholars most cited alongside Bei Guo, 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 36 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Epigenetic regulation in metabolic diseases: mechanisms and advances in clinical study Hit paper breakdown → | 2023 | 222 |
| 2 | 2020 | 117 | |
| 3 | 2021 | 54 | |
| 4 | 2021 | 53 | |
| 5 | 2018 | 51 | |
| 6 | 2020 | 48 | |
| 7 | 2022 | 47 | |
| 8 | 2020 | 43 | |
| 9 | 2019 | 40 | |
| 10 | 2021 | 33 | |
| 11 | 2021 | 31 | |
| 12 | 2020 | 30 | |
| 13 | 2020 | 27 | |
| 14 | 2016 | 27 | |
| 15 | 2022 | 25 | |
| 16 | 2019 | 24 | |
| 17 | 2020 | 23 | |
| 18 | 2021 | 23 | |
| 19 | 2020 | 21 | |
| 20 | 2020 | 20 |
About Bei Guo
Bei Guo is a scholar working on Molecular Biology, Cancer Research, Epidemiology, Cardiology and Cardiovascular Medicine and Physiology, having authored 36 papers that have together received 1.1k indexed citations. Recurring topics across this work include Extracellular vesicles in disease (14 papers), MicroRNA in disease regulation (10 papers), RNA modifications and cancer (4 papers), Cardiovascular Disease and Adiposity (4 papers), Adipose Tissue and Metabolism (4 papers), Mesenchymal stem cell research (3 papers), Circular RNAs in diseases (3 papers) and Adipokines, Inflammation, and Metabolic Diseases (3 papers). The work is most often cited by research in Cancer Research (275 citations), Nephrology (114 citations), Molecular Biology (626 citations), Aging (13 citations) and Genetics (71 citations). Bei Guo has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include Ling‐Qing Yuan, Su‐Kang Shan, Fu‐Xing‐Zi Li, Ming-Hui Zheng, Xiao Lin, Feng Xu, Feng Wu, Jia‐Yu Zhong, Qiu-Shuang Xu and Changchun Li. Their work appears in journals such as Frontiers in Endocrinology, Frontiers in Cell and Developmental Biology, Journal of Nanobiotechnology, Cell Death and Disease and Obesity Reviews.
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.