Kai Gan
Impact in
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- Cancer-related molecular mechanisms research
- MicroRNA in disease regulation
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- RNA modifications and cancer
- Advanced biosensing and bioanalysis techniques
- RNA Interference and Gene Delivery
- Circular RNAs in diseases
- Ubiquitin and proteasome pathways
Papers in
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- Signaling Pathways in Disease 3
- Bone Metabolism and Diseases 3
- Epigenetics and DNA Methylation 2
- RNA Research and Splicing 2
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- NF-κB Signaling Pathways 3
- Cancer, Lipids, and Metabolism 2
- Cancer-related molecular mechanisms research 2
- Co-authors
- Guiyuan Li (8 shared papers)Bin Xu (3 shared papers)Shourong Shen (5 shared papers)Wei Tong (1 shared paper)Minghua Wu (4 shared papers)Qiong Chen (3 shared papers)Xiaoling Li (3 shared papers)Zhaoyang Zeng (3 shared papers)
In The Last Decade
Kai Gan
19 papers receiving 287 citations
Peers
Comparison fields: 5 of 73
- Cancer Research 54
- Molecular Biology 184
- Cell Biology 33
- Transplantation 5
- Oncology 44
Countries citing papers authored by Kai Gan
This map shows the geographic impact of Kai Gan'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 Gan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kai Gan more than expected).
Fields of papers citing papers by Kai Gan
This network shows the impact of papers produced by Kai Gan. 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 Gan. The network helps show where Kai Gan may publish in the future.
Co-authors
The 25 scholars most cited alongside Kai Gan, 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 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2006 | 47 | |
| 2 | 2005 | 41 | |
| 3 | 2005 | 31 | |
| 4 | 2007 | 28 | |
| 5 | 2021 | 24 | |
| 6 | 2021 | 21 | |
| 7 | 2006 | 17 | |
| 8 | 2023 | 17 | |
| 9 | 2021 | 13 | |
| 10 | 2021 | 11 | |
| 11 | 2024 | 10 | |
| 12 | 2022 | 7 | |
| 13 | 2024 | 7 | |
| 14 | 2023 | 6 | |
| 15 | 2005 | 5 | |
| 16 | [In vitro gene transfection by magnetic iron oxide nanoparticles and magnetic field increases transfection efficiency]. | 2004 | 4 |
| 17 | 2024 | 2 | |
| 18 | 2022 | 1 | |
| 19 | [Biocompatibility of poly-l-lysine-modified silica nanoparticles]. | 2003 | 1 |
| 20 | 2025 | 0 |
About Kai Gan
Kai Gan is a scholar working on Molecular Biology, Cancer Research, Oncology, Surgery and Pharmacology, having authored 22 papers that have together received 293 indexed citations. Recurring topics across this work include Signaling Pathways in Disease (3 papers), NF-κB Signaling Pathways (3 papers), Bone Metabolism and Diseases (3 papers), Cancer, Lipids, and Metabolism (2 papers), Epigenetics and DNA Methylation (2 papers), RNA Research and Splicing (2 papers), Cancer-related molecular mechanisms research (2 papers) and Power System Optimization and Stability (2 papers). The work is most often cited by research in Cancer Research (54 citations), Molecular Biology (184 citations), Cell Biology (33 citations), Transplantation (5 citations) and Oncology (44 citations). Kai Gan has collaborated with scholars based in China and Australia. Frequent co-authors include Guiyuan Li, Bin Xu, Shourong Shen, Wei Tong, Minghua Wu, Qiong Chen, Xiaoling Li, Zhaoyang Zeng, Yunlian Tang and Qiuhong Zhang. Their work appears in journals such as Energies, Journal of Translational Medicine, Cell Death Discovery, Phytotherapy Research and FEBS Letters.
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.