Yun Gao
- Molecular Biology top 1%
- Cancer Research top 1%
- Oncology top 2%
- Physiology top 2%
- Rheumatology top 1%
- Co-authors
- Akira YamaguchiRoderick T. BronsonShusaku YoshikiYukihiko KitamuraKoichi SasakiMotohiko SatoT KishimotoShogo Nomura
- Topics
- Adenosine and Purinergic Signaling (50 papers)Pain Mechanisms and Treatments (35 papers)Cancer-related molecular mechanisms research (21 papers)
- Journals
- CellProceedings of the National Academy of SciencesSHILAP Revista de lepidopterología
- Partner nations
- ChinaSingaporeUnited States
In The Last Decade
Yun Gao
119 papers receiving 7.1k citations
Hit Papers
Peers
Comparison fields: 5 of 136
- Molecular Biology 4.3k
- Cancer Research 1.3k
- Oncology 1.2k
- Physiology 999
- Rheumatology 891
Countries citing papers authored by Yun Gao
This map shows the geographic impact of Yun Gao'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 Yun Gao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yun Gao more than expected).
Fields of papers citing papers by Yun Gao
This network shows the impact of papers produced by Yun Gao. 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 Yun Gao. The network helps show where Yun Gao may publish in the future.
Co-authorship network of co-authors of Yun Gao
This figure shows the co-authorship network connecting the top 25 collaborators of Yun Gao. A scholar is included among the top collaborators of Yun Gao based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yun Gao. Yun Gao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 13 | |
| 2 | 2 | |
| 3 | 2 | |
| 4 | 7 | |
| 5 | 32 | |
| 6 | 52 | |
| 7 | 18 | |
| 8 | 13 | |
| 9 | 11 | |
| 10 | 26 | |
| 11 | 26 | |
| 12 | 113 | |
| 13 | 30 | |
| 14 | 44 | |
| 15 | 13 | |
| 16 | Effect of Sodium Ferulate on platelet activition and blood rheology in type 2 diabetes | 1 |
| 17 | Suppression Effect of Brassica Campestris Pollen Extract on the Growth of Prostate Cancer Cell in vitro | 2 |
| 18 | 11 | |
| 19 | [Pigment epithelium-derived factor gene therapy inhibits the growth of transplanted human hepatocellular carcinoma in nude mice]. | 2 |
| 20 | 32 |
About Yun Gao
Yun Gao is a scholar working on Physiology, Endocrine and Autonomic Systems and Cancer Research, having authored 121 papers that have together received 7.2k indexed citations. Recurring topics across this work include Adenosine and Purinergic Signaling (50 papers), Pain Mechanisms and Treatments (35 papers) and Cancer-related molecular mechanisms research (21 papers). The work is most often cited by research in Physiology (778 citations), Cancer Research (1.3k citations) and Molecular Biology (4.3k citations). Yun Gao has collaborated with scholars based in China, Singapore and United States. Frequent co-authors include Akira Yamaguchi, Roderick T. Bronson, Shusaku Yoshiki, Yukihiko Kitamura, Koichi Sasaki, Motohiko Sato, T Kishimoto, Shogo Nomura, Ryoko Okamoto and Toshihisa Komori. Their work appears in journals such as Cell, Proceedings of the National Academy of Sciences and SHILAP Revista de lepidopterología.
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.