Chun-Cai Gu
Impact in
- Cancer Research top 5%
- Cancer-related molecular mechanisms research
- MicroRNA in disease regulation
- Physiology top 10%
Papers in
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- Cancer-related molecular mechanisms research 8
- Cancer, Hypoxia, and Metabolism 3
- MicroRNA in disease regulation 2
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- RNA modifications and cancer 3
- RNA Research and Splicing 2
- Natural product bioactivities and synthesis 1
- Epigenetics and DNA Methylation 1
- Co-authors
- Side Liu (10 shared papers)Yuxin Fang (7 shared papers)Qingyuan Li (6 shared papers)Qun Yan (6 shared papers)Xinke Wang (5 shared papers)Qiuhua Lai (7 shared papers)Yue Zhang (5 shared papers)Jianqun Cai (4 shared papers)
- Journals
- Cell Death and Disease (4 papers)Aging (2 papers)Cancer Letters (1 paper)Clinical Cancer Research (1 paper)Gut Microbes (1 paper)
- Partner nations
- ChinaUnited States
In The Last Decade
Chun-Cai Gu
17 papers receiving 878 citations
Peers
Comparison fields: 5 of 82
- Cancer Research 416
- Physiology 38
- Molecular Biology 539
- Oncology 123
- Immunology 59
Countries citing papers authored by Chun-Cai Gu
This map shows the geographic impact of Chun-Cai Gu'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 Chun-Cai Gu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chun-Cai Gu more than expected).
Fields of papers citing papers by Chun-Cai Gu
This network shows the impact of papers produced by Chun-Cai Gu. 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 Chun-Cai Gu. The network helps show where Chun-Cai Gu may publish in the future.
Co-authors
The 25 scholars most cited alongside Chun-Cai Gu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 172 | |
| 2 | 2018 | 139 | |
| 3 | 2019 | 89 | |
| 4 | 2019 | 88 | |
| 5 | 2020 | 85 | |
| 6 | 2020 | 72 | |
| 7 | 2022 | 39 | |
| 8 | 2020 | 33 | |
| 9 | 2018 | 30 | |
| 10 | 2017 | 30 | |
| 11 | 2020 | 30 | |
| 12 | 2016 | 25 | |
| 13 | 2021 | 21 | |
| 14 | 2021 | 14 | |
| 15 | 2023 | 10 | |
| 16 | 2017 | 5 | |
| 17 | 2024 | 4 |
About Chun-Cai Gu
Chun-Cai Gu is a scholar working on Cancer Research, Molecular Biology, Pathology and Forensic Medicine, Oncology and Immunology, having authored 17 papers that have together received 886 indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (8 papers), RNA modifications and cancer (3 papers), Cancer, Hypoxia, and Metabolism (3 papers), RNA Research and Splicing (2 papers), MicroRNA in disease regulation (2 papers), Genetic factors in colorectal cancer (2 papers), Natural product bioactivities and synthesis (1 paper) and Epigenetics and DNA Methylation (1 paper). The work is most often cited by research in Cancer Research (416 citations), Physiology (38 citations), Molecular Biology (539 citations), Oncology (123 citations) and Immunology (59 citations). Chun-Cai Gu has collaborated with scholars based in China and United States. Frequent co-authors include Side Liu, Yuxin Fang, Qingyuan Li, Qun Yan, Xinke Wang, Qiuhua Lai, Yue Zhang, Jianqun Cai, Juan He and Lu Han. Their work appears in journals such as Cell Death and Disease, Aging, Cancer Letters, Clinical Cancer Research and Gut Microbes.
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.