Yongzhen Mo

6.6k total citations · 6 hit papers
38 papers, 4.1k citations indexed

About

Yongzhen Mo is a scholar working on Molecular Biology, Cancer Research and Oncology. According to data from OpenAlex, Yongzhen Mo has authored 38 papers receiving a total of 4.1k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Molecular Biology, 22 papers in Cancer Research and 11 papers in Oncology. Recurrent topics in Yongzhen Mo's work include Cancer-related molecular mechanisms research (15 papers), Circular RNAs in diseases (14 papers) and RNA modifications and cancer (12 papers). Yongzhen Mo is often cited by papers focused on Cancer-related molecular mechanisms research (15 papers), Circular RNAs in diseases (14 papers) and RNA modifications and cancer (12 papers). Yongzhen Mo collaborates with scholars based in China, United States and Saudi Arabia. Yongzhen Mo's co-authors include Zhaoyang Zeng, Guiyuan Li, Wei Xiong, Yong Li, Can Guo, Xiaoling Li, Fang Xiong, Qianjin Liao, Peng Miao and Xiaoling Li and has published in prestigious journals such as ACS Nano, Cancer Research and Oncogene.

In The Last Decade

Yongzhen Mo

37 papers receiving 4.1k citations

Hit Papers

Circular RNAs function as... 2018 2026 2020 2023 2018 2019 2020 2021 2020 250 500 750

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Yongzhen Mo 2.9k 2.2k 959 907 291 38 4.1k
Sabine Hoves 1.5k 0.5× 1.2k 0.5× 1.8k 1.9× 1.1k 1.2× 250 0.9× 33 3.6k
Sascha Keller 3.9k 1.4× 2.0k 0.9× 733 0.8× 435 0.5× 160 0.5× 41 4.8k
Jianjun Zhang 3.5k 1.2× 2.4k 1.1× 494 0.5× 721 0.8× 359 1.2× 113 4.6k
Alessandra Carè 2.5k 0.9× 1.1k 0.5× 866 0.9× 605 0.7× 237 0.8× 95 4.1k
Zahra Madjd 1.9k 0.7× 931 0.4× 1.0k 1.1× 1.7k 1.8× 477 1.6× 174 4.0k
Jingjing Zhao 1.9k 0.7× 1.5k 0.7× 285 0.3× 399 0.4× 325 1.1× 104 2.8k
Lin Jia 1.7k 0.6× 962 0.4× 440 0.5× 1.1k 1.2× 431 1.5× 117 3.2k
Peng Wang 2.0k 0.7× 1.2k 0.5× 444 0.5× 415 0.5× 198 0.7× 182 3.1k
James R. Hammond 2.6k 0.9× 1.3k 0.6× 328 0.3× 458 0.5× 120 0.4× 66 3.7k
Bing Chen 2.0k 0.7× 1.2k 0.5× 375 0.4× 470 0.5× 231 0.8× 151 3.1k

Countries citing papers authored by Yongzhen Mo

Since Specialization
Citations

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

Fields of papers citing papers by Yongzhen Mo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yongzhen Mo

This figure shows the co-authorship network connecting the top 25 collaborators of Yongzhen Mo. A scholar is included among the top collaborators of Yongzhen Mo 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 Yongzhen Mo. Yongzhen Mo 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.
Huang, Mao, Yixuan Liu, Qijia Yan, et al.. (2024). NK cells as powerful therapeutic tool in cancer immunotherapy. Cellular Oncology. 47(3). 733–757. 4 indexed citations
2.
Zhi, Yuan, Yongzhen Mo, Yumin Wang, et al.. (2023). Spatially Resolved Transcriptomics Technology Facilitates Cancer Research. Advanced Science. 10(30). e2302558–e2302558. 22 indexed citations
3.
Wu, Pan, Xiangchan Hou, Peng Miao, et al.. (2023). Circular RNA circRILPL1 promotes nasopharyngeal carcinoma malignant progression by activating the Hippo-YAP signaling pathway. Cell Death and Differentiation. 30(7). 1679–1694. 29 indexed citations
4.
Ren, Daixi, Yongzhen Mo, Mei Yang, et al.. (2023). Emerging roles of tRNA in cancer. Cancer Letters. 563. 216170–216170. 19 indexed citations
5.
Wang, Yian, Qijia Yan, Chunmei Fan, et al.. (2023). Overview and countermeasures of cancer burden in China. Science China Life Sciences. 66(11). 2515–2526. 86 indexed citations breakdown →
6.
Chen, Shiyin, Qiwen Wu, Lingyun Liu, et al.. (2023). CD155 and its receptors in cancer immune escape and immunotherapy. Cancer Letters. 573. 216381–216381. 28 indexed citations
7.
Wang, Yian, Qijia Yan, Yongzhen Mo, et al.. (2022). Splicing factor derived circular RNA circCAMSAP1 accelerates nasopharyngeal carcinoma tumorigenesis via a SERPINH1/c-Myc positive feedback loop. Molecular Cancer. 21(1). 62–62. 52 indexed citations
8.
Ge, Junshang, Jie Wang, Fang Xiong, et al.. (2021). Epstein–Barr Virus–Encoded Circular RNA CircBART2.2 Promotes Immune Escape of Nasopharyngeal Carcinoma by Regulating PD-L1. Cancer Research. 81(19). 5074–5088. 113 indexed citations
9.
Zhu, Kunjie, Junshang Ge, Yi He, et al.. (2021). Bioinformatics Analysis of the Signaling Pathways and Genes of Gossypol Induce Death of Nasopharyngeal Carcinoma Cells. DNA and Cell Biology. 40(8). 1052–1063. 3 indexed citations
10.
Jiang, Xianjie, Xiangying Deng, Jie Wang, et al.. (2021). BPIFB1 inhibits vasculogenic mimicry via downregulation of GLUT1-mediated H3K27 acetylation in nasopharyngeal carcinoma. Oncogene. 41(2). 233–245. 20 indexed citations
11.
Mo, Yongzhen, Yumin Wang, Shuai Zhang, et al.. (2021). Circular RNA circRNF13 inhibits proliferation and metastasis of nasopharyngeal carcinoma via SUMO2. Molecular Cancer. 20(1). 112–112. 94 indexed citations
12.
Ren, Daixi, Yuze Hua, Boyao Yu, et al.. (2020). Predictive biomarkers and mechanisms underlying resistance to PD1/PD-L1 blockade cancer immunotherapy. Molecular Cancer. 19(1). 19–19. 218 indexed citations
13.
Wu, Pan, Yongzhen Mo, Peng Miao, et al.. (2020). Emerging role of tumor-related functional peptides encoded by lncRNA and circRNA. Molecular Cancer. 19(1). 22–22. 412 indexed citations breakdown →
14.
Mo, Yongzhen, Yumin Wang, Fang Xiong, et al.. (2019). Proteomic Analysis of the Molecular Mechanism of Lovastatin Inhibiting the Growth of Nasopharyngeal Carcinoma Cells. Journal of Cancer. 10(10). 2342–2349. 32 indexed citations
15.
Mo, Yongzhen, Yumin Wang, Lishen Zhang, et al.. (2019). The role of Wnt signaling pathway in tumor metabolic reprogramming. Journal of Cancer. 10(16). 3789–3797. 88 indexed citations
16.
Miao, Peng, Yongzhen Mo, Yian Wang, et al.. (2019). Neoantigen vaccine: an emerging tumor immunotherapy. Molecular Cancer. 18(1). 128–128. 524 indexed citations breakdown →
17.
Ge, Junshang, Jie Wang, Xianjie Jiang, et al.. (2019). The BRAF V600E mutation is a predictor of the effect of radioiodine therapy in papillary thyroid cancer. Journal of Cancer. 11(4). 932–939. 50 indexed citations
18.
Jin, Ke, Shufei Wang, Yazhuo Zhang, et al.. (2019). Long non-coding RNA PVT1 interacts with MYC and its downstream molecules to synergistically promote tumorigenesis. Cellular and Molecular Life Sciences. 76(21). 4275–4289. 107 indexed citations
19.
Wang, Yian, Xiaoling Li, Yongzhen Mo, et al.. (2018). Effects of tumor metabolic microenvironment on regulatory T cells. Molecular Cancer. 17(1). 143 indexed citations
20.
Wang, Yumin, Yongzhen Mo, Zhaojian Gong, et al.. (2017). Circular RNAs in human cancer. Molecular Cancer. 16(1). 25–25. 309 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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