Fei Xing

581 total citations
24 papers, 401 citations indexed

About

Fei Xing is a scholar working on Molecular Biology, Oncology and Immunology. According to data from OpenAlex, Fei Xing has authored 24 papers receiving a total of 401 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 11 papers in Oncology and 9 papers in Immunology. Recurrent topics in Fei Xing's work include interferon and immune responses (7 papers), Immune Response and Inflammation (5 papers) and Cytokine Signaling Pathways and Interactions (5 papers). Fei Xing is often cited by papers focused on interferon and immune responses (7 papers), Immune Response and Inflammation (5 papers) and Cytokine Signaling Pathways and Interactions (5 papers). Fei Xing collaborates with scholars based in China, Japan and United States. Fei Xing's co-authors include Huaijun Liu, Songyun Zhang, Chunxia Wang, Hongli Gao, Xin Guan, Tadaatsu Imaizumi, Ryo Hayakari, Jinqi Xue, Hidemi Yoshida and Tomoh Matsumiya and has published in prestigious journals such as The Journal of Immunology, PLoS ONE and Biomaterials.

In The Last Decade

Fei Xing

24 papers receiving 394 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Fei Xing China 13 175 93 65 55 43 24 401
Osnat Almogi‐Hazan Israel 11 171 1.0× 178 1.9× 27 0.4× 27 0.5× 15 0.3× 22 522
Koushi Fujisawa Japan 10 190 1.1× 160 1.7× 65 1.0× 19 0.3× 26 0.6× 17 570
Laura Johnson Australia 9 108 0.6× 155 1.7× 33 0.5× 13 0.2× 11 0.3× 19 382
Chengcheng Guo China 13 195 1.1× 143 1.5× 102 1.6× 12 0.2× 17 0.4× 48 508
Ariel Finkielsztein United States 9 220 1.3× 150 1.6× 60 0.9× 9 0.2× 33 0.8× 12 433
Junko Murata Japan 11 143 0.8× 27 0.3× 32 0.5× 19 0.3× 7 0.2× 31 596
Alexander Benz Germany 10 178 1.0× 34 0.4× 33 0.5× 10 0.2× 63 1.5× 14 414
Melanie Howell United States 13 335 1.9× 61 0.7× 84 1.3× 14 0.3× 6 0.1× 19 695
Bradford E. Hall United States 8 148 0.8× 143 1.5× 46 0.7× 8 0.1× 17 0.4× 11 435

Countries citing papers authored by Fei Xing

Since Specialization
Citations

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

Fields of papers citing papers by Fei Xing

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fei Xing

This figure shows the co-authorship network connecting the top 25 collaborators of Fei Xing. A scholar is included among the top collaborators of Fei Xing 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 Fei Xing. Fei Xing 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.
Жакыпбек, Ырысжан, Qingdong Shi, Fei Xing, et al.. (2025). In Silico Analysis of miRNA-mRNA Binding Sites in Arabidopsis thaliana as a Model for Drought-Tolerant Plants. Plants. 14(12). 1800–1800. 2 indexed citations
2.
Gao, Hongli, Mu Li, Xin Guan, et al.. (2025). Unlocking the potential of chimeric antigen receptor T cell engineering immunotherapy: Long road to achieve precise targeted therapy for hepatobiliary pancreatic cancers. International Journal of Biological Macromolecules. 297. 139829–139829. 1 indexed citations
3.
Xing, Fei, et al.. (2025). Antibody-oligonucleotide conjugates in cancer therapy: Potential and Promise. Critical Reviews in Oncology/Hematology. 215. 104858–104858. 4 indexed citations
4.
Zou, Chen‐Yu, Han Chen, Fei Xing, et al.. (2024). Smart design in biopolymer-based hemostatic sponges: From hemostasis to multiple functions. Bioactive Materials. 45. 459–478. 12 indexed citations
5.
Gao, Hongli, Zhuo Xi, Jinqi Xue, et al.. (2024). Drug resistance mechanisms and treatment strategies mediated by Ubiquitin-Specific Proteases (USPs) in cancers: new directions and therapeutic options. Molecular Cancer. 23(1). 88–88. 31 indexed citations
6.
Gao, Hongli, Zhiguang Chen, Liang Zhao, Ce Ji, & Fei Xing. (2024). Cellular functions, molecular signalings and therapeutic applications: Translational potential of deubiquitylating enzyme USP9X as a drug target in cancer treatment. Biochimica et Biophysica Acta (BBA) - Reviews on Cancer. 1879(3). 189099–189099. 12 indexed citations
7.
Fan, Ming‐Hui, Xiuzhen Zhang, Yanlin Jiang, et al.. (2024). Exosomes from hypoxic urine-derived stem cells facilitate healing of diabetic wound by targeting SERPINE1 through miR-486-5p. Biomaterials. 314. 122893–122893. 26 indexed citations
8.
Gao, Hongli, Ce Ji, Xiaopeng Yu, et al.. (2023). Targeting ubiquitin specific proteases (USPs) in cancer immunotherapy: from basic research to preclinical application. Journal of Experimental & Clinical Cancer Research. 42(1). 225–225. 59 indexed citations
9.
Gao, Hongli, Xin Guan, Shuang Zhang, et al.. (2023). CMTM6 as a potential therapy target is associated with immunological tumor microenvironment and can promote migration and invasion in pancreatic adenocarcinoma. Functional & Integrative Genomics. 23(4). 306–306. 1 indexed citations
10.
Xing, Fei, Tomoh Matsumiya, Ryo Hayakari, et al.. (2016). Alteration of Antiviral Signalling by Single Nucleotide Polymorphisms (SNPs) of Mitochondrial Antiviral Signalling Protein (MAVS). PLoS ONE. 11(3). e0151173–e0151173. 17 indexed citations
11.
Matsumiya, Tomoh, Ryo Hayakari, Ken Furudate, et al.. (2015). Retinoic acid-inducible gene-I-like receptor (RLR)-mediated antiviral innate immune responses in the lower respiratory tract: Roles of TRAF3 and TRAF5. Biochemical and Biophysical Research Communications. 467(2). 191–196. 4 indexed citations
12.
Imaizumi, Tadaatsu, Hidemi Yoshida, Ryo Hayakari, et al.. (2015). Desferrioxamine, an iron chelator, inhibits CXCL10 expression induced by polyinosinic–polycytidylic acid in U373MG human astrocytoma cells. Neuroscience Research. 94. 10–16. 12 indexed citations
13.
14.
Imaizumi, Tadaatsu, Akihiko Numata, Hidemi Yoshida, et al.. (2014). ISG54 and ISG56 are induced by TLR3 signaling in U373MG human astrocytoma cells: Possible involvement in CXCL10 expression. Neuroscience Research. 84. 34–42. 23 indexed citations
15.
16.
Liu, Huaijun, et al.. (2014). Brain structural changes and their correlation with vascular disease in type 2 diabetes mellitus patients: a voxel-based morphometric study. Neural Regeneration Research. 9(16). 1548–1548. 28 indexed citations
17.
Imaizumi, Tadaatsu, Tomomi Aizawa‐Yashiro, Tomoh Matsumiya, et al.. (2013). Interaction between Interferon-Stimulated Gene 56 and Melanoma Differentiation-Associated Gene 5 in Toll-Like Receptor 3 Signaling in Normal Human Mesangial Cells. American Journal of Nephrology. 37(2). 118–125. 12 indexed citations
18.
Imaizumi, Tadaatsu, Tomoh Matsumiya, Ryo Hayakari, et al.. (2013). MDA5 and ISG56 mediate CXCL10 expression induced by Toll-like receptor 4 activation in U373MG human astrocytoma cells. Neuroscience Research. 76(4). 195–206. 22 indexed citations
19.
Wang, Jian, Yujia Zhou, Dapeng Feng, et al.. (2011). CD86 +1057G/A Polymorphism and Susceptibility to Ewing's Sarcoma: A Case–Control Study. DNA and Cell Biology. 31(4). 537–540. 11 indexed citations
20.
Xing, Fei, et al.. (1994). Effects of Cisplatin and its Analogues on the Permeabilityof Human Erythrocyte Membrane. Metal-Based Drugs. 2(2). 73–80. 8 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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