Shaojun Yu

1.6k total citations
58 papers, 711 citations indexed

About

Shaojun Yu is a scholar working on Molecular Biology, Oncology and Pathology and Forensic Medicine. According to data from OpenAlex, Shaojun Yu has authored 58 papers receiving a total of 711 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 12 papers in Oncology and 7 papers in Pathology and Forensic Medicine. Recurrent topics in Shaojun Yu's work include Genetic factors in colorectal cancer (3 papers), MicroRNA in disease regulation (3 papers) and Cancer-related molecular mechanisms research (3 papers). Shaojun Yu is often cited by papers focused on Genetic factors in colorectal cancer (3 papers), MicroRNA in disease regulation (3 papers) and Cancer-related molecular mechanisms research (3 papers). Shaojun Yu collaborates with scholars based in China, United States and South Korea. Shaojun Yu's co-authors include Kang Ning, Runzhi Zhang, Hong Bai, Lifeng Sun, Pengshuo Yang, Maozhen Han, Chaofang Zhong, Hongjun Li, Guofeng Chen and Jian Wang and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Shaojun Yu

47 papers receiving 704 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Shaojun Yu China 14 368 169 95 70 66 58 711
Shaoqiang Zhang China 16 325 0.9× 127 0.8× 128 1.3× 54 0.8× 62 0.9× 55 666
Xuguang Hu China 15 379 1.0× 163 1.0× 107 1.1× 106 1.5× 90 1.4× 48 814
Ning Gu China 17 346 0.9× 120 0.7× 69 0.7× 78 1.1× 104 1.6× 57 808
Chengtao Sun China 17 363 1.0× 125 0.7× 114 1.2× 82 1.2× 72 1.1× 43 723
Yini Xu China 21 408 1.1× 133 0.8× 87 0.9× 90 1.3× 108 1.6× 80 932
Peiwu Li China 17 309 0.8× 175 1.0× 78 0.8× 114 1.6× 70 1.1× 37 659
Man Xu China 17 355 1.0× 103 0.6× 62 0.7× 66 0.9× 53 0.8× 29 713
Heran Wang China 11 388 1.1× 179 1.1× 187 2.0× 47 0.7× 48 0.7× 24 686
Xing Wei China 19 493 1.3× 174 1.0× 121 1.3× 103 1.5× 86 1.3× 67 979
Miaomiao Dai China 15 346 0.9× 115 0.7× 131 1.4× 50 0.7× 44 0.7× 31 659

Countries citing papers authored by Shaojun Yu

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Shaojun Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Shaojun Yu. A scholar is included among the top collaborators of Shaojun Yu 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 Shaojun Yu. Shaojun Yu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Yu, Shaojun, Josiah Hiu-yuen Wong, Juan Wang, et al.. (2025). The 3D Genome Browser 2.0: an enhanced online platform for visualizing and analyzing 3D genome architecture. Nucleic Acids Research. 54(D1). D48–D54.
2.
Zheng, Zhiyuan, Shaojun Yu, Fumiko Chino, et al.. (2025). Cancer-Related Crowdfunding Economy in the United States. Journal of the National Comprehensive Cancer Network. 23(11).
3.
4.
Liu, Yongjian, et al.. (2025). Synthesis of harmaline N-9 derivatives and investigation of in vitro anticancer activity. Bioorganic & Medicinal Chemistry Letters. 119. 130106–130106.
5.
Zheng, Yuyan, Jingjing Zhang, Chao Chen, et al.. (2024). Prophylactic hyperthermic intraperitoneal chemotherapy in T4 colorectal cancer: Can it improve the oncologic prognosis? – A propensity score matching study. European Journal of Surgical Oncology. 50(2). 107958–107958.
6.
Yang, Baocheng, et al.. (2024). Emerging industry classification based on BERT model. Information Systems. 128. 102484–102484. 3 indexed citations
7.
Zhang, Mingqi, Guofeng Chen, Xiaoli Jin, Jun Wang, & Shaojun Yu. (2024). Pre-Operative Immunonutrition Enhances Postoperative Outcomes and Elevates Tumor-Infiltrating Lymphocyte Counts in Colorectal Cancer Patients: A Meta-Analysis of Randomized Controlled Trials. Nutrition and Cancer. 76(6). 499–512. 6 indexed citations
8.
Yu, Shaojun, et al.. (2024). A novel classification framework for genome-wide association study of whole brain MRI images using deep learning. PLoS Computational Biology. 20(10). e1012527–e1012527.
9.
Yu, Shaojun, et al.. (2024). UI/UX for Generative AI: Taxonomy, Trend, and Challenge. IEEE Access. 12. 179891–179911. 5 indexed citations
10.
Yu, Shaojun, Weixing Dai, Senlin Zhao, et al.. (2023). Function and mechanism of MCM8 in the development and progression of colorectal cancer. Journal of Translational Medicine. 21(1). 623–623. 6 indexed citations
11.
Zhang, Jing, Shaojun Yu, Xuan Li, et al.. (2023). SPLIT: Stance and Persuasion Prediction with Multi-modal on Image and Textual Information. 175–180. 1 indexed citations
12.
Kan, Xuan, Zimu Li, Hejie Cui, et al.. (2023). R-Mixup: Riemannian Mixup for Biological Networks. PubMed. 2023. 1073–1085. 1 indexed citations
13.
Zhou, Haiyan, et al.. (2023). Comparison of short-term surgical outcomes and long-term survival between emergency and elective surgery for colorectal cancer: a systematic review and meta-analysis. International Journal of Colorectal Disease. 38(1). 41–41. 9 indexed citations
14.
Wang, Jun, Beidi Wang, Biting Zhou, et al.. (2022). A novel immune-related lncRNA pair signature for prognostic prediction and immune response evaluation in gastric cancer: a bioinformatics and biological validation study. Cancer Cell International. 22(1). 69–69. 7 indexed citations
15.
Huang, Yanting, Xiaobo Sun, Shaojun Yu, et al.. (2021). A machine learning approach to brain epigenetic analysis reveals kinases associated with Alzheimer’s disease. Nature Communications. 12(1). 4472–4472. 38 indexed citations
16.
Wang, Jun, Shaojun Yu, Guofeng Chen, et al.. (2020). A novel prognostic signature of immune‐related genes for patients with colorectal cancer. Journal of Cellular and Molecular Medicine. 24(15). 8491–8504. 44 indexed citations
17.
Chen, Chao, Jian Wang, Xiaoxu Ge, et al.. (2020). <p>Factors Prognostic for Peritoneal Metastases from Colorectal Cancer Treated with Surgery</p>. Cancer Management and Research. Volume 12. 10587–10602. 3 indexed citations
18.
Chen, Wei, Zhouqi Li, Hao Liu, et al.. (2020). MicroRNA-30a targets BECLIN-1 to inactivate autophagy and sensitizes gastrointestinal stromal tumor cells to imatinib. Cell Death and Disease. 11(3). 198–198. 51 indexed citations
19.
Yu, Shaojun, Haiting Xie, Jingjing Zhang, et al.. (2017). MicroRNA-663 suppresses the proliferation and invasion of colorectal cancer cells by directly targeting FSCN1. Molecular Medicine Reports. 16(6). 9707–9714. 17 indexed citations
20.
Yu, Shaojun. (1997). Comparative study on proliferation activity in small hepatocellular carcinoma related to hepatitis virus B and C. World Journal of Gastroenterology. 3(4). 236–236. 5 indexed citations

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.

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