Song Chen
- Cancer Research top 2%
- MicroRNA in disease regulation 17
- Cancer-related molecular mechanisms research 13
- Neurology top 2%
- Neuroinflammation and Neurodegeneration Mechanisms 10
- Biological Psychiatry top 5%
- Molecular Biology top 2%
- Epigenetics and DNA Methylation 16
- RNA modifications and cancer 14
- Neurology top 2%
- Neuroinflammation and Neurodegeneration Mechanisms 10
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- Autophagy in Disease and Therapy 16
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- Hepatocellular Carcinoma Treatment and Prognosis 11
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- Radiomics and Machine Learning in Medical Imaging 11
- Co-authors
- Hongkui DengJun‐Lin GuanJ LianJulio Herrero GarcíaYuki YoshidaWei JiangYan ShiSyn Kok Yeo
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Song Chen
309 papers receiving 7.4k citations
Peers
Comparison fields: 5 of 189
- Cancer Research 841
- Neurology 396
- Biological Psychiatry 101
- Molecular Biology 2.7k
- Neurology 512
Countries citing papers authored by Song Chen
This map shows the geographic impact of Song Chen'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 Song Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Song Chen more than expected).
Fields of papers citing papers by Song Chen
This network shows the impact of papers produced by Song Chen. 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 Song Chen. The network helps show where Song Chen may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Song Chen, 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 | 2025 | 0 | |
| 2 | 2025 | 2 | |
| 3 | 2024 | 2 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 6 | |
| 6 | 2024 | 5 | |
| 7 | 2023 | 7 | |
| 8 | 2023 | 31 | |
| 9 | 2023 | 7 | |
| 10 | 2023 | 14 | |
| 11 | 2023 | 3 | |
| 12 | 2023 | 1 | |
| 13 | ALP Inhibitors Inhibit Inflammatory Responses and Osteoblast Differentiation in hVIC via AKT-ERK Pathways. | 2023 | 2 |
| 14 | 2021 | 9 | |
| 15 | 2021 | 0 | |
| 16 | 2020 | 26 | |
| 17 | 2018 | 17 | |
| 18 | 2016 | 111 | |
| 19 | 2013 | 49 | |
| 20 | 2013 | 24 |
About Song Chen
Song Chen is a scholar working on Biological Psychiatry, Cancer Research and Transplantation, having authored 329 papers that have together received 7.5k indexed citations. Recurring topics across this work include MicroRNA in disease regulation (17 papers), Autophagy in Disease and Therapy (16 papers), Epigenetics and DNA Methylation (16 papers), RNA modifications and cancer (14 papers), Cancer-related molecular mechanisms research (13 papers), Hepatocellular Carcinoma Treatment and Prognosis (11 papers), Radiomics and Machine Learning in Medical Imaging (11 papers) and Neuroinflammation and Neurodegeneration Mechanisms (10 papers). The work is most often cited by research in Cancer Research (841 citations), Neurology (396 citations) and Biological Psychiatry (101 citations). Song Chen has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Hongkui Deng, Jun‐Lin Guan, J Lian, Julio Herrero García, Yuki Yoshida, Wei Jiang, Yan Shi, Syn Kok Yeo, Xin Sui and Meng Liu. Their work appears in journals such as PLoS ONE, Scientific Reports, Frontiers in Oncology, Theranostics and Cancer Research.
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.