Congjian Xu

6.3k total citations · 2 hit papers
158 papers, 4.9k citations indexed

About

Congjian Xu is a scholar working on Molecular Biology, Reproductive Medicine and Cancer Research. According to data from OpenAlex, Congjian Xu has authored 158 papers receiving a total of 4.9k indexed citations (citations by other indexed papers that have themselves been cited), including 88 papers in Molecular Biology, 43 papers in Reproductive Medicine and 36 papers in Cancer Research. Recurrent topics in Congjian Xu's work include Ovarian cancer diagnosis and treatment (24 papers), Endometriosis Research and Treatment (18 papers) and Reproductive System and Pregnancy (15 papers). Congjian Xu is often cited by papers focused on Ovarian cancer diagnosis and treatment (24 papers), Endometriosis Research and Treatment (18 papers) and Reproductive System and Pregnancy (15 papers). Congjian Xu collaborates with scholars based in China, United States and Japan. Congjian Xu's co-authors include Fuyou Li, Liqin Xiong, Xiaoyan Zhang, Yang Yang, Tianshe Yang, Fan Zhang, Haiou Liu, Tianye Cao, Qiwei Tian and Zhigang Chen and has published in prestigious journals such as Nature Communications, PLoS ONE and Biomaterials.

In The Last Decade

Congjian Xu

153 papers receiving 4.8k citations

Hit Papers

Long-term in vivo biodistribution imaging and toxicity of... 2010 2026 2015 2020 2010 2018 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Congjian Xu China 35 2.1k 1.3k 1.3k 873 755 158 4.9k
Annette T. Byrne Ireland 28 1.6k 0.8× 994 0.8× 1.4k 1.1× 827 0.9× 1.2k 1.6× 71 4.8k
Marcel Garcia France 45 2.7k 1.3× 1.1k 0.8× 1.1k 0.9× 1.5k 1.7× 1.2k 1.5× 146 6.2k
Zhenfeng Duan United States 50 3.7k 1.8× 901 0.7× 1.1k 0.8× 1.5k 1.7× 2.2k 2.9× 131 7.4k
Bénédicte F. Jordan Belgium 42 2.5k 1.2× 627 0.5× 850 0.7× 2.5k 2.9× 689 0.9× 127 6.1k
Patrycja Nowak‐Sliwinska Switzerland 39 1.9k 0.9× 649 0.5× 1.1k 0.9× 835 1.0× 1.8k 2.3× 101 5.0k
Sherry Y. Wu United States 29 2.6k 1.2× 232 0.2× 829 0.7× 725 0.8× 464 0.6× 66 4.4k
M. Guillaume Wientjes United States 42 2.6k 1.2× 231 0.2× 1.2k 0.9× 644 0.7× 1.3k 1.7× 129 6.2k
Olga B. Garbuzenko United States 32 2.5k 1.2× 410 0.3× 1.1k 0.9× 356 0.4× 504 0.7× 49 4.6k
Simon T. Barry United Kingdom 38 2.8k 1.3× 350 0.3× 1.5k 1.2× 685 0.8× 1.4k 1.8× 123 6.1k

Countries citing papers authored by Congjian Xu

Since Specialization
Citations

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

Fields of papers citing papers by Congjian Xu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Congjian Xu

This figure shows the co-authorship network connecting the top 25 collaborators of Congjian Xu. A scholar is included among the top collaborators of Congjian Xu 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 Congjian Xu. Congjian Xu 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.
He, Mengdi, Chenyang Wang, Xueling Wang, et al.. (2025). Mannose Enhances Immunotherapy Efficacy in Ovarian Cancer by Modulating Gut Microbial Metabolites. Cancer Research. 85(13). 2468–2484. 3 indexed citations
2.
Xu, Congjian, et al.. (2024). Clinical characteristics and status of treatment of small-cell carcinoma of the ovary, hypercalcemic type in the Chinese population: a meta-analysis. Journal of Gynecologic Oncology. 35(4). e96–e96. 2 indexed citations
3.
Fan, Deng‐Xuan, et al.. (2023). Growth Hormone Promotes Oocyte Maturation In Vitro by Protecting Mitochondrial Function and Reducing Apoptosis. Reproductive Sciences. 30(7). 2219–2230. 3 indexed citations
4.
Liu, Qiyu, Xiaobo Zhou, Wei Yuan, et al.. (2023). A follicle-stimulating hormone receptor-targeted near-infrared fluorescent probe for tumor-selective imaging and photothermal therapy. Materials Today Bio. 24. 100904–100904. 7 indexed citations
5.
Xu, Congjian, et al.. (2022). Tackling cellular senescence by targeting miRNAs. Biogerontology. 23(4). 387–400. 7 indexed citations
6.
7.
Ohno, Yuko, et al.. (2020). Rosiglitazone ameliorates senescence and promotes apoptosis in ovarian cancer induced by olaparib. Cancer Chemotherapy and Pharmacology. 85(2). 273–284. 15 indexed citations
8.
Zhang, Guodong, Jiaqi Lu, Moran Yang, et al.. (2019). Elevated GALNT10 expression identifies immunosuppressive microenvironment and dismal prognosis of patients with high grade serous ovarian cancer. Cancer Immunology Immunotherapy. 69(2). 175–187. 23 indexed citations
9.
Lin, Xiaojuan, Jianfeng Shen, Dan Peng, et al.. (2018). RNA-binding protein LIN28B inhibits apoptosis through regulation of the AKT2/FOXO3A/BIM axis in ovarian cancer cells. Signal Transduction and Targeted Therapy. 3(1). 23–23. 45 indexed citations
10.
Wu, Zhi‐Yong, et al.. (2018). FGFRL1 Promotes Ovarian Cancer Progression by Crosstalk with Hedgehog Signaling. Journal of Immunology Research. 2018. 1–11. 15 indexed citations
11.
Liu, Haiou, et al.. (2018). Olaparib induced senescence under P16 or P53 dependent manner in ovarian cancer. Journal of Gynecologic Oncology. 30(2). e26–e26. 26 indexed citations
12.
Yang, Qin, Zhi‐Yong Wu, Suan Sun, et al.. (2018). PD-L1 Expression Predicts a Distinct Prognosis in Krukenberg Tumor with Corresponding Origins. Journal of Immunology Research. 2018. 1–10. 14 indexed citations
13.
Li, Yanyun, Qingqing Cai, Lin Lin, & Congjian Xu. (2018). MiR-875 and miR-3144 switch the human papillomavirus 16 E6/E6* mRNA ratio through the EGFR pathway and a direct targeting effect. Gene. 679. 389–397. 5 indexed citations
14.
Zhao, Ran, Wenjun Qin, Jing Han, et al.. (2017). Lectin array and glycogene expression analyses of ovarian cancer cell line A2780 and its cisplatin-resistant derivate cell line A2780-cp. Clinical Proteomics. 14(1). 20–20. 30 indexed citations
15.
Yu, Yi, Xiaoyan Zhang, Mingxing Zhang, et al.. (2014). Epidermal growth factor induces platelet-activating factor production through receptors transactivation and cytosolic phospholipase A2 in ovarian cancer cells. Journal of Ovarian Research. 7(1). 39–39. 19 indexed citations
16.
Hu, Jun, Lirong Zhu, Liang Zhi-qing, et al.. (2011). Clinical outcomes of fertility-sparing treatments in young patients with epithelial ovarian carcinoma. Journal of Zhejiang University SCIENCE B. 12(10). 787–795. 23 indexed citations
17.
Zhang, Xiaoyan, Jun Chen, Yufang Zheng, et al.. (2009). Follicle-Stimulating Hormone Peptide Can Facilitate Paclitaxel Nanoparticles to Target Ovarian Carcinoma In vivo. Cancer Research. 69(16). 6506–6514. 80 indexed citations
18.
Xiong, Liqin, Mengxiao Yu, Meng Zhang, et al.. (2009). A photostable fluorescent probe for targeted imaging of tumour cells possessing integrin αvβ3**. Molecular BioSystems. 5(3). 241–243. 27 indexed citations
19.
Liu, Y., et al.. (2009). Algoriphagus aquatilis sp. nov., isolated from a freshwater lake. INTERNATIONAL JOURNAL OF SYSTEMATIC AND EVOLUTIONARY MICROBIOLOGY. 59(7). 1759–1763. 43 indexed citations
20.
Lu, Hongxia, Bin Li, Yu Kang, et al.. (2006). Paclitaxel nanoparticle inhibits growth of ovarian cancer xenografts and enhances lymphatic targeting. Cancer Chemotherapy and Pharmacology. 59(2). 175–181. 50 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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