Juxiang Chen

3.7k total citations · 1 hit paper
76 papers, 2.6k citations indexed

About

Juxiang Chen is a scholar working on Molecular Biology, Genetics and Cancer Research. According to data from OpenAlex, Juxiang Chen has authored 76 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Molecular Biology, 24 papers in Genetics and 18 papers in Cancer Research. Recurrent topics in Juxiang Chen's work include Glioma Diagnosis and Treatment (23 papers), RNA modifications and cancer (13 papers) and MicroRNA in disease regulation (10 papers). Juxiang Chen is often cited by papers focused on Glioma Diagnosis and Treatment (23 papers), RNA modifications and cancer (13 papers) and MicroRNA in disease regulation (10 papers). Juxiang Chen collaborates with scholars based in China, United States and Germany. Juxiang Chen's co-authors include Yicheng Lu, Hongxiang Wang, Tao Xu, Yong Yan, Guohan Hu, Qilin Huang, A. John Iafrate, Chun Luo, Long P. Le and Juliann Chmielecki and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Nature Medicine.

In The Last Decade

Juxiang Chen

73 papers receiving 2.6k citations

Hit Papers

Anchored multiplex PCR for targeted next-generation seque... 2014 2026 2018 2022 2014 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Juxiang Chen China 29 1.5k 864 544 496 457 76 2.6k
Jiří Ehrmann Czechia 24 1.3k 0.9× 655 0.8× 284 0.5× 777 1.6× 275 0.6× 113 2.6k
Erik J. Uhlmann United States 30 1.7k 1.1× 447 0.5× 589 1.1× 734 1.5× 383 0.8× 73 3.4k
Fengju Chen United States 26 1.6k 1.1× 703 0.8× 553 1.0× 680 1.4× 278 0.6× 62 3.1k
Ulf D. Kahlert Germany 27 1.3k 0.9× 830 1.0× 183 0.3× 563 1.1× 589 1.3× 99 2.4k
Tiziana Annese Italy 30 1.7k 1.2× 772 0.9× 326 0.6× 800 1.6× 211 0.5× 99 3.2k
Deric M. Park United States 26 861 0.6× 490 0.6× 299 0.5× 543 1.1× 568 1.2× 54 2.1k
Chuanlu Jiang China 33 2.1k 1.4× 1.6k 1.8× 265 0.5× 336 0.7× 574 1.3× 72 3.0k
Myung Jin Son South Korea 24 1.8k 1.2× 757 0.9× 198 0.4× 763 1.5× 638 1.4× 54 3.1k
Nabendu Pore United States 17 1.4k 0.9× 1.1k 1.2× 287 0.5× 614 1.2× 181 0.4× 26 2.3k
Bassem R. Haddad United States 33 2.4k 1.6× 718 0.8× 466 0.9× 1.0k 2.0× 157 0.3× 81 4.4k

Countries citing papers authored by Juxiang Chen

Since Specialization
Citations

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

Fields of papers citing papers by Juxiang Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Juxiang Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Juxiang Chen. A scholar is included among the top collaborators of Juxiang Chen 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 Juxiang Chen. Juxiang Chen 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.
2.
Li, Rong, Ning Ji, Han Liu, et al.. (2025). Brain-targeting drug delivery systems: The state of the art in treatment of glioblastoma. Materials Today Bio. 30. 101443–101443. 13 indexed citations
3.
Cheng, Lilin, Zhongrun Qian, Chao Chen, et al.. (2024). AGBL4 promotes malignant progression of glioblastoma via modulation of MMP-1 and inflammatory pathways. Frontiers in Immunology. 15. 1420182–1420182.
4.
Lei, Huan, Hongxiang Wang, Lei Qi, et al.. (2024). Dysregulated inter-mitochondrial crosstalk in glioblastoma cells revealed by in situ cryo-electron tomography. Proceedings of the National Academy of Sciences. 121(9). e2311160121–e2311160121. 6 indexed citations
5.
Yang, Dan, Binbin Nie, Jin‐Gang He, et al.. (2024). Exploring cerebral structural and functional abnormalities in a mouse model of post-traumatic headache induced by mild traumatic brain injury. 动物学研究. 45(3). 648–662. 2 indexed citations
6.
Chen, Chao, Yue Liu, Hongxiang Wang, et al.. (2023). FOXO1-miR-506 axis promotes chemosensitivity to temozolomide and suppresses invasiveness in glioblastoma through a feedback loop of FOXO1/miR-506/ETS1/FOXO1. Journal of Zhejiang University SCIENCE B. 24(8). 698–710. 4 indexed citations
7.
Liu, Yue, Chao Chen, Xinye Wang, et al.. (2022). An Epigenetic Role of Mitochondria in Cancer. Cells. 11(16). 2518–2518. 93 indexed citations
8.
Chen, Juxiang, et al.. (2021). Multifocal glioblastoma—two case reports and literature review. Chinese Neurosurgical Journal. 7(1). 8–8. 3 indexed citations
9.
Wang, Hongxiang, Tao Xu, Qilin Huang, Weilin Jin, & Juxiang Chen. (2020). Immunotherapy for Malignant Glioma: Current Status and Future Directions. Trends in Pharmacological Sciences. 41(2). 123–138. 121 indexed citations
10.
Chen, Yihong, Hongxiang Wang, Cong Tan, et al.. (2018). Expression of amyloid precursor-like protein 2 (APLP2) in glioblastoma is associated with patient prognosis. Folia Neuropathologica. 56(1). 30–38. 10 indexed citations
11.
Meng, Wei, Jiajia Wang, Baocheng Wang, et al.. (2018). CDK7 inhibition is a novel therapeutic strategy against GBM both in vitro and in vivo. Cancer Management and Research. Volume 10. 5747–5758. 31 indexed citations
12.
Wang, Hongxiang, Rong Qin, Jian Mao, et al.. (2018). CPEB4 regulates glioblastoma cell proliferation and predicts poor outcome of patients. Clinical Neurology and Neurosurgery. 169. 92–97. 5 indexed citations
13.
Wakimoto, Hiroaki, Shota Tanaka, William T. Curry, et al.. (2014). Targetable Signaling Pathway Mutations Are Associated with Malignant Phenotype in IDH -Mutant Gliomas. Clinical Cancer Research. 20(11). 2898–2909. 130 indexed citations
15.
Xu, Tao, Rong Qin, Yong Yan, et al.. (2012). Overexpression of Golgi phosphoprotein-3 (GOLPH3) in glioblastoma multiforme is associated with worse prognosis. Journal of Neuro-Oncology. 110(2). 195–203. 55 indexed citations
16.
Xu, Tao, Quan Zhou, Jingxu Zhou, et al.. (2011). Carboxyl terminus of Hsp70‐interacting protein (CHIP) contributes to human glioma oncogenesis. Cancer Science. 102(5). 959–966. 36 indexed citations
17.
Xu, Tao, Juxiang Chen, Yicheng Lu, & Johannes Wolff. (2010). Effects of bevacizumab plus irinotecan on response and survival in patients with recurrent malignant glioma: a systematic review and survival-gain analysis. BMC Cancer. 10(1). 252–252. 46 indexed citations
18.
Chen, Juxiang, et al.. (2004). Expression and Function of Differentially Expressed Genes in Glioblastoma by Using cDNA Microarray. Academic Journal of Second Military Medical University. 25(5). 498–502. 1 indexed citations
19.
Chen, Juxiang, Jian Xu, Kang Ying, et al.. (2004). Molecular cloning and characterization of a novel human BTB domain-containing gene, BTBD10, which is down-regulated in glioma. Gene. 340(1). 61–69. 25 indexed citations
20.
Li, Yao, Yali Li, Rong Tang, et al.. (2002). Discovery and analysis of hepatocellular carcinoma genes using cDNA microarrays. Journal of Cancer Research and Clinical Oncology. 128(7). 369–379. 55 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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