Kai Gan
Impact in
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- Cancer-related molecular mechanisms research
- MicroRNA in disease regulation
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- Advanced biosensing and bioanalysis techniques
- Bone Metabolism and Diseases
- RNA modifications and cancer
- RNA Interference and Gene Delivery
- Ubiquitin and proteasome pathways
Papers in
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- NF-κB Signaling Pathways 3
- Cancer-related molecular mechanisms research 2
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- Signaling Pathways in Disease 3
- RNA Research and Splicing 3
- Bone Metabolism and Diseases 3
- Co-authors
- Guiyuan Li (6 shared papers)Wei Tong (1 shared paper)Bin Xu (3 shared papers)Shourong Shen (4 shared papers)Qiong Chen (3 shared papers)Minghua Wu (4 shared papers)Zhaoyang Zeng (2 shared papers)Yunlian Tang (3 shared papers)
In The Last Decade
Kai Gan
22 papers receiving 335 citations
Peers
Comparison fields: 5 of 74
- Cancer Research 44
- Molecular Biology 166
- Transplantation 5
- Oncology 45
- Cell Biology 27
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 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2006 | 49 | |
| 2 | 2005 | 47 | |
| 3 | 2007 | 30 | |
| 4 | 2021 | 29 | |
| 5 | 2005 | 29 | |
| 6 | 2023 | 28 | |
| 7 | 2021 | 26 | |
| 8 | 2024 | 18 | |
| 9 | 2006 | 17 | |
| 10 | 2021 | 13 | |
| 11 | 2021 | 13 | |
| 12 | 2024 | 10 | |
| 13 | 2023 | 9 | |
| 14 | 2022 | 7 | |
| 15 | 2005 | 5 | |
| 16 | 2025 | 3 | |
| 17 | 2025 | 2 | |
| 18 | 2025 | 2 | |
| 19 | 2024 | 2 | |
| 20 | 2025 | 1 |
About Kai Gan
Kai Gan is a scholar working on Cancer Research, Molecular Biology, Cellular and Molecular Neuroscience, Control and Systems Engineering and Oncology, having authored 23 papers that have together received 342 indexed citations. Recurring topics across this work include NF-κB Signaling Pathways (3 papers), Signaling Pathways in Disease (3 papers), RNA Research and Splicing (3 papers), Bone Metabolism and Diseases (3 papers), Axon Guidance and Neuronal Signaling (2 papers), Cancer-related molecular mechanisms research (2 papers), Power Systems Fault Detection (2 papers) and Cancer-related Molecular Pathways (2 papers). The work is most often cited by research in Cancer Research (44 citations), Molecular Biology (166 citations), Transplantation (5 citations), Oncology (45 citations) and Cell Biology (27 citations). Kai Gan has collaborated with scholars based in China, Australia and India. Frequent co-authors include Guiyuan Li, Wei Tong, Bin Xu, Shourong Shen, Qiong Chen, Minghua Wu, Zhaoyang Zeng, Yunlian Tang, Xiaoling Li and Qiuhong Zhang. Their work appears in journals such as Energies, Journal of Translational Medicine, Frontiers in Oncology, Journal of Nanoscience and Nanotechnology and Journal of Nanobiotechnology.
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.