Jun Song
Impact in
- Cancer Research top 2%
- Cancer-related molecular mechanisms research
- MicroRNA in disease regulation
- Physiology top 5%
Papers in
-
- Cancer-related molecular mechanisms research 14
- MicroRNA in disease regulation 7
-
- Adenosine and Purinergic Signaling 6
- Co-authors
- Yi ZhangJin BaiSong HuYunze LiuTao JiangPei-Cong ShiPingfu HouYixin Xu
- Journals
- Cell Death and Disease (4 papers)Journal of Experimental & Clinical Cancer Research (3 papers)BioMed Research International (2 papers)International Immunopharmacology (2 papers)Frontiers in Oncology (2 papers)
- Partner nations
- ChinaSouth KoreaUnited States
In The Last Decade
Jun Song
64 papers receiving 1.6k citations
Hit Papers
Peers
Comparison fields: 5 of 89
- Cancer Research 675
- Physiology 84
- Oncology 449
- Molecular Biology 990
- Immunology 175
Countries citing papers authored by Jun Song
This map shows the geographic impact of Jun Song'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 Jun Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Song more than expected).
Fields of papers citing papers by Jun Song
This network shows the impact of papers produced by Jun Song. 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 Jun Song. The network helps show where Jun Song may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Song, 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 | 2024 | 1 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 0 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 1 | |
| 6 | 2022 | 16 | |
| 7 | 2022 | 3 | |
| 8 | 2021 | 4 | |
| 9 | 2021 | 7 | |
| 10 | 2021 | 4 | |
| 11 | 2020 | 46 | |
| 12 | 2019 | 60 | |
| 13 | 2019 | 15 | |
| 14 | 2018 | 77 | |
| 15 | 2018 | 38 | |
| 16 | 2018 | 13 | |
| 17 | 2018 | 101 | |
| 18 | 2017 | 17 | |
| 19 | 2017 | 0 | |
| 20 | Kaiyuqingre formula improves insulin secretion via regulating uncoupling protein-2 and KATP channel. | 2011 | 6 |
About Jun Song
Jun Song is a scholar working on Cancer Research, Physiology, Oncology, Applied Microbiology and Biotechnology and Molecular Biology, having authored 69 papers that have together received 1.6k indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (14 papers), RNA modifications and cancer (13 papers), MicroRNA in disease regulation (7 papers), Adenosine and Purinergic Signaling (6 papers), Cancer Cells and Metastasis (5 papers), Cancer-related gene regulation (5 papers), Immune Cell Function and Interaction (5 papers) and RNA Research and Splicing (5 papers). The work is most often cited by research in Cancer Research (675 citations), Physiology (84 citations), Oncology (449 citations), Molecular Biology (990 citations) and Immunology (175 citations). Jun Song has collaborated with scholars based in China, South Korea and United States. Frequent co-authors include Yi Zhang, Jin Bai, Song Hu, Yunze Liu, Tao Jiang, Pei-Cong Shi, Pingfu Hou, Yixin Xu, Mo Kang and Insoon Chang. Their work appears in journals such as Cell Death and Disease, Journal of Experimental & Clinical Cancer Research, BioMed Research International, International Immunopharmacology and Frontiers in Oncology.
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.