Weiwei Gui
Impact in
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- Cancer-related molecular mechanisms research
- MicroRNA in disease regulation
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- Circular RNAs in diseases
- RNA modifications and cancer
- RNA Research and Splicing
- Epigenetics and DNA Methylation
Papers in
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- Circular RNAs in diseases 4
- Metabolism, Diabetes, and Cancer 3
- RNA modifications and cancer 2
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- Cancer-related molecular mechanisms research 5
- MicroRNA in disease regulation 3
- Cancer, Hypoxia, and Metabolism 3
- Co-authors
- Xihua Lin (20 shared papers)Hong Li (12 shared papers)Yiyi Zhu (4 shared papers)Fenping Zheng (8 shared papers)Fang Wu (5 shared papers)Shengjie Tang (3 shared papers)Yiping Zhu (2 shared papers)Xueyao Yin (2 shared papers)
- Journals
- Experimental Cell Research (2 papers)Journal of Molecular Cell Biology (2 papers)Diabetes (1 paper)Poultry Science (1 paper)Frontiers in Endocrinology (1 paper)
- Partner nations
- China
In The Last Decade
Weiwei Gui
24 papers receiving 325 citations
Peers
Comparison fields: 5 of 55
- Cancer Research 132
- Molecular Biology 193
- Physiology 46
- Geriatrics and Gerontology 5
- Endocrinology, Diabetes and Metabolism 24
Countries citing papers authored by Weiwei Gui
This map shows the geographic impact of Weiwei Gui'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 Weiwei Gui with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Weiwei Gui more than expected).
Fields of papers citing papers by Weiwei Gui
This network shows the impact of papers produced by Weiwei Gui. 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 Weiwei Gui. The network helps show where Weiwei Gui may publish in the future.
Co-authors
The 25 scholars most cited alongside Weiwei Gui, 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 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 75 | |
| 2 | 2020 | 31 | |
| 3 | 2021 | 24 | |
| 4 | 2021 | 23 | |
| 5 | 2021 | 23 | |
| 6 | 2020 | 18 | |
| 7 | 2022 | 16 | |
| 8 | 2021 | 15 | |
| 9 | 2020 | 15 | |
| 10 | 2020 | 14 | |
| 11 | 2020 | 11 | |
| 12 | 2023 | 9 | |
| 13 | 2020 | 8 | |
| 14 | 2021 | 8 | |
| 15 | 2020 | 8 | |
| 16 | 2022 | 8 | |
| 17 | 2020 | 6 | |
| 18 | 2021 | 5 | |
| 19 | 2021 | 4 | |
| 20 | 2024 | 3 |
About Weiwei Gui
Weiwei Gui is a scholar working on Molecular Biology, Cancer Research, Physiology, Endocrinology, Diabetes and Metabolism and Surgery, having authored 27 papers that have together received 328 indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (5 papers), Circular RNAs in diseases (4 papers), Adipose Tissue and Metabolism (4 papers), Metabolism, Diabetes, and Cancer (3 papers), MicroRNA in disease regulation (3 papers), Cancer, Hypoxia, and Metabolism (3 papers), RNA modifications and cancer (2 papers) and Blood groups and transfusion (1 paper). The work is most often cited by research in Cancer Research (132 citations), Molecular Biology (193 citations), Physiology (46 citations), Geriatrics and Gerontology (5 citations) and Endocrinology, Diabetes and Metabolism (24 citations). Weiwei Gui has collaborated with scholars based in China. Frequent co-authors include Xihua Lin, Hong Li, Yiyi Zhu, Fenping Zheng, Fang Wu, Shengjie Tang, Yiping Zhu, Xueyao Yin, Yiyi Zhu and Hong Li. Their work appears in journals such as Experimental Cell Research, Journal of Molecular Cell Biology, Diabetes, Poultry Science and Frontiers in Endocrinology.
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.