Jun Dai

1.7k total citations · 1 hit paper
24 papers, 1.2k citations indexed

About

Jun Dai is a scholar working on Molecular Biology, Cancer Research and Rheumatology. According to data from OpenAlex, Jun Dai has authored 24 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 8 papers in Cancer Research and 7 papers in Rheumatology. Recurrent topics in Jun Dai's work include Osteoarthritis Treatment and Mechanisms (7 papers), Single-cell and spatial transcriptomics (5 papers) and Cancer-related molecular mechanisms research (4 papers). Jun Dai is often cited by papers focused on Osteoarthritis Treatment and Mechanisms (7 papers), Single-cell and spatial transcriptomics (5 papers) and Cancer-related molecular mechanisms research (4 papers). Jun Dai collaborates with scholars based in China, Finland and United States. Jun Dai's co-authors include Hongwei Ouyang, Boon Chin Heng, Dongsheng Yu, Hua Liu, Xiaohui Zou, Shouan Zhu, Jing Zhou, Fang Zhou, Bingbing Wu and Zhiming Liu and has published in prestigious journals such as Nucleic Acids Research, Angewandte Chemie International Edition and Nature Communications.

In The Last Decade

Jun Dai

23 papers receiving 1.2k citations

Hit Papers

Exosomes from embryonic mesenchymal stem cells alleviate ... 2017 2026 2020 2023 2017 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jun Dai China 13 593 379 262 168 149 24 1.2k
Rama Murthy Garimella India 16 431 0.7× 151 0.4× 155 0.6× 97 0.6× 70 0.5× 53 1.1k
Zhuqing Jia China 25 879 1.5× 108 0.3× 296 1.1× 376 2.2× 382 2.6× 68 1.8k
Yan Kang China 20 948 1.6× 380 1.0× 740 2.8× 135 0.8× 206 1.4× 71 1.6k
Shidong Jia United States 16 1.2k 2.1× 59 0.2× 512 2.0× 251 1.5× 151 1.0× 71 2.0k
Dong‐Guk Shin United States 16 786 1.3× 74 0.2× 142 0.5× 106 0.6× 95 0.6× 66 1.3k
Yongping Li China 20 387 0.7× 305 0.8× 166 0.6× 115 0.7× 160 1.1× 99 1.4k
Hui Jing China 15 286 0.5× 60 0.2× 137 0.5× 55 0.3× 128 0.9× 42 704
Marten A. Engelse Netherlands 31 1.5k 2.5× 123 0.3× 414 1.6× 97 0.6× 1.6k 10.7× 81 3.4k

Countries citing papers authored by Jun Dai

Since Specialization
Citations

This map shows the geographic impact of Jun Dai'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 Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Dai more than expected).

Fields of papers citing papers by Jun Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jun Dai. 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 Dai. The network helps show where Jun Dai may publish in the future.

Co-authorship network of co-authors of Jun Dai

This figure shows the co-authorship network connecting the top 25 collaborators of Jun Dai. A scholar is included among the top collaborators of Jun Dai 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 Jun Dai. Jun Dai 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.
Dong, Jiantong, Jun Dai, Xiaoding Lou, et al.. (2025). Light‐Triggered CRISPR/Cas12a for Genomic Editing and Tumor Regression. Angewandte Chemie International Edition. 64(28). e202502892–e202502892. 4 indexed citations
2.
Wu, Jiani, Zhujun Liu, Xiaolong Li, et al.. (2025). Photocontrolled dissociation and toehold-mediated strand displacement-based synergistic regulation of CRISPR-Cas12a. Nucleic Acids Research. 53(20).
3.
Katainen, Riku, Jun Dai, Anna Vähärautio, et al.. (2025). Drug-tolerant persisting polyploid giant cancer cells mediate resistance to HER2-targeting antibody-drug conjugates. Cancer Letters. 630. 217900–217900. 2 indexed citations
4.
Jamalzadeh, Sanaz, Jun Dai, Yilin Li, et al.. (2024). Genome-wide quantification of copy-number aberration impact on gene expression in ovarian high-grade serous carcinoma. BMC Cancer. 24(1). 173–173. 2 indexed citations
5.
Dai, Jun, Shuyu Zheng, Matías Marín Falco, et al.. (2024). Tracing back primed resistance in cancer via sister cells. Nature Communications. 15(1). 1158–1158. 7 indexed citations
6.
Tang, Weicheng, Dan Chen, Jiaqiang Xiong, et al.. (2024). Multiomics insights into the female reproductive aging. Ageing Research Reviews. 95. 102245–102245. 18 indexed citations
7.
Chen, Ying, Shuhao Yang, Jinjin Zhang, et al.. (2023). Spatial omics: An innovative frontier in aging research. Ageing Research Reviews. 93. 102158–102158. 7 indexed citations
8.
Wu, Tong, Yan Li, Jun Dai, et al.. (2022). Construction of a competing endogenous RNA network to identify drug targets against polycystic ovary syndrome. Human Reproduction. 37(12). 2856–2866. 3 indexed citations
9.
Zhang, Kaiyang, Erdoğan Pekcan Erkan, Sanaz Jamalzadeh, et al.. (2022). Longitudinal single-cell RNA-seq analysis reveals stress-promoted chemoresistance in metastatic ovarian cancer. Science Advances. 8(8). eabm1831–eabm1831. 93 indexed citations
10.
Häkkinen, Antti, Kaiyang Zhang, Amjad Alkodsi, et al.. (2021). PRISM: recovering cell-type-specific expression profiles from individual composite RNA-seq samples. Bioinformatics. 37(18). 2882–2888. 11 indexed citations
11.
Sun, Heng, Xiaolei Zhang, Jun Dai, et al.. (2020). Sodium lactate promotes stemness of human mesenchymal stem cells through KDM6B mediated glycolytic metabolism. Biochemical and Biophysical Research Communications. 532(3). 433–439. 12 indexed citations
12.
Wang, Yafei, Jiayun Huang, Lin Gong, et al.. (2019). The Plasticity of Mesenchymal Stem Cells in Regulating Surface HLA-I. iScience. 15. 66–78. 42 indexed citations
13.
Yu, Dongsheng, Zhi-yong Sheng, Guotong Fu, et al.. (2019). Dual roles of misshapen/NIK-related kinase (MINK1) in osteoarthritis subtypes through the activation of TGFβ signaling. Osteoarthritis and Cartilage. 28(1). 112–121. 13 indexed citations
14.
Wang, Yafei, Dongsheng Yu, Zhiming Liu, et al.. (2017). Exosomes from embryonic mesenchymal stem cells alleviate osteoarthritis through balancing synthesis and degradation of cartilage extracellular matrix. Stem Cell Research & Therapy. 8(1). 189–189. 366 indexed citations breakdown →
15.
Dai, Jun, Dongsheng Yu, Yafei Wang, et al.. (2017). Kdm6b regulates cartilage development and homeostasis through anabolic metabolism. Annals of the Rheumatic Diseases. 76(7). 1295–1303. 59 indexed citations
16.
Yu, Dongsheng, et al.. (2016). Regulation of gut commensal flora attenuates osteoarthritis through interleukin 17. Journal of Orthopaedic Translation. 7. 133–133. 1 indexed citations
17.
Zhang, Xiaolei, Yan Wu, Zongyou Pan, et al.. (2016). The effects of lactate and acid on articular chondrocytes function: Implications for polymeric cartilage scaffold design. Acta Biomaterialia. 42. 329–340. 46 indexed citations
18.
Chen, Pengfei, Shouan Zhu, Youzhi Cai, et al.. (2014). Radially oriented collagen scaffold with SDF-1 promotes osteochondral repair by facilitating cell homing. Biomaterials. 39. 114–123. 164 indexed citations
19.
Dai, Jun. (2011). Study on Motion of Underwater Towed Missile Launch System. Acta Armamentarii. 1 indexed citations
20.
Dai, Jun & Qin Meng. (2011). Differential function of protective agents at each stage of the hypothermic preservation of hepatocytes. The Journal of Biochemistry. 149(6). 739–745. 9 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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