Shaojun Yu
Impact in
- Cancer Research top 10%
- Cancer-related molecular mechanisms research
- MicroRNA in disease regulation
- Pharmacology top 10%
- Pharmacological Effects of Natural Compounds
Papers in
-
- RNA Research and Splicing 2
- Oncology 12
- Co-authors
- Kang Ning (5 shared papers)Hong Bai (1 shared paper)Runzhi Zhang (1 shared paper)Lifeng Sun (8 shared papers)Pengshuo Yang (3 shared papers)Maozhen Han (3 shared papers)Chaofang Zhong (2 shared papers)Guofeng Chen (4 shared papers)
- Journals
- Scientific Reports (2 papers)JCO Oncology Practice (2 papers)World Journal of Surgical Oncology (2 papers)Cancer Management and Research (2 papers)International Journal of Biological Macromolecules (1 paper)
- Partner nations
- ChinaUnited StatesSouth Korea
In The Last Decade
Shaojun Yu
47 papers receiving 704 citations
Peers
Comparison fields: 5 of 124
- Cancer Research 169
- Pharmacology 64
- Complementary and alternative medicine 60
- Molecular Biology 368
- Oncology 95
Countries citing papers authored by Shaojun Yu
This map shows the geographic impact of Shaojun Yu'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 Shaojun Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shaojun Yu more than expected).
Fields of papers citing papers by Shaojun Yu
This network shows the impact of papers produced by Shaojun Yu. 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 Shaojun Yu. The network helps show where Shaojun Yu may publish in the future.
Co-authors
The 25 scholars most cited alongside Shaojun Yu, 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 58 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 159 | |
| 2 | 2019 | 55 | |
| 3 | 2020 | 51 | |
| 4 | 2018 | 47 | |
| 5 | 2020 | 44 | |
| 6 | 2021 | 38 | |
| 7 | 2015 | 38 | |
| 8 | 2019 | 37 | |
| 9 | 2019 | 26 | |
| 10 | 2019 | 18 | |
| 11 | 2017 | 17 | |
| 12 | 2021 | 15 | |
| 13 | 2024 | 14 | |
| 14 | 2022 | 14 | |
| 15 | 2018 | 10 | |
| 16 | 2015 | 10 | |
| 17 | 2023 | 9 | |
| 18 | 2017 | 8 | |
| 19 | 2022 | 8 | |
| 20 | 2022 | 7 |
About Shaojun Yu
Shaojun Yu is a scholar working on Molecular Biology, Oncology, Pathology and Forensic Medicine, Cancer Research and Surgery, having authored 58 papers that have together received 711 indexed citations. Recurring topics across this work include Genetic factors in colorectal cancer (3 papers), FinTech, Crowdfunding, Digital Finance (3 papers), Cancer Mechanisms and Therapy (3 papers), MicroRNA in disease regulation (3 papers), Cancer-related molecular mechanisms research (3 papers), Hepatocellular Carcinoma Treatment and Prognosis (2 papers), Gastrointestinal Tumor Research and Treatment (2 papers) and RNA Research and Splicing (2 papers). The work is most often cited by research in Cancer Research (169 citations), Pharmacology (64 citations), Complementary and alternative medicine (60 citations), Molecular Biology (368 citations) and Oncology (95 citations). Shaojun Yu has collaborated with scholars based in China, United States and South Korea. Frequent co-authors include Kang Ning, Hong Bai, Runzhi Zhang, Lifeng Sun, Pengshuo Yang, Maozhen Han, Chaofang Zhong, Guofeng Chen, Hongjun Li and Jianwei Wang. Their work appears in journals such as Scientific Reports, JCO Oncology Practice, World Journal of Surgical Oncology, Cancer Management and Research and International Journal of Biological Macromolecules.
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.