Yuejun Fu

1.3k total citations
90 papers, 1.0k citations indexed

About

Yuejun Fu is a scholar working on Molecular Biology, Insect Science and Genetics. According to data from OpenAlex, Yuejun Fu has authored 90 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 66 papers in Molecular Biology, 21 papers in Insect Science and 14 papers in Genetics. Recurrent topics in Yuejun Fu's work include Insect Resistance and Genetics (32 papers), Viral Infectious Diseases and Gene Expression in Insects (25 papers) and Entomopathogenic Microorganisms in Pest Control (10 papers). Yuejun Fu is often cited by papers focused on Insect Resistance and Genetics (32 papers), Viral Infectious Diseases and Gene Expression in Insects (25 papers) and Entomopathogenic Microorganisms in Pest Control (10 papers). Yuejun Fu collaborates with scholars based in China, United States and Czechia. Yuejun Fu's co-authors include Aihua Liang, Shuhua Zheng, Litian Yin, Na An, Xiaojun Fan, Yali Zheng, Rui Huang, Na An, Changchen Hu and Wei Wang and has published in prestigious journals such as SHILAP Revista de lepidopterología, Applied and Environmental Microbiology and Chemical Communications.

In The Last Decade

Yuejun Fu

81 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yuejun Fu China 17 632 173 149 110 99 90 1.0k
Norbert Bakalara France 24 1.3k 2.0× 59 0.3× 81 0.5× 39 0.4× 102 1.0× 46 1.9k
Tomoko Komiyama Japan 18 821 1.3× 140 0.8× 177 1.2× 71 0.6× 45 0.5× 38 1.3k
Gunn‐Guang Liou Taiwan 20 1.0k 1.6× 226 1.3× 98 0.7× 44 0.4× 43 0.4× 46 1.5k
Filip Jeleń Poland 13 783 1.2× 73 0.4× 54 0.4× 70 0.6× 26 0.3× 15 1.1k
Karl‐Heinz Gührs Germany 23 1.2k 1.9× 107 0.6× 261 1.8× 123 1.1× 34 0.3× 45 1.9k
Joyce Chiu Australia 18 759 1.2× 90 0.5× 54 0.4× 45 0.4× 33 0.3× 38 1.3k
Hyung Ho Lee South Korea 21 1.0k 1.6× 161 0.9× 52 0.3× 123 1.1× 16 0.2× 93 1.5k
Kęstutis Sužiedėlis Lithuania 16 526 0.8× 110 0.6× 226 1.5× 32 0.3× 70 0.7× 48 920
Carol Perez‐Iratxeta Canada 10 744 1.2× 97 0.6× 54 0.4× 79 0.7× 32 0.3× 13 1.1k

Countries citing papers authored by Yuejun Fu

Since Specialization
Citations

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

Fields of papers citing papers by Yuejun Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yuejun Fu

This figure shows the co-authorship network connecting the top 25 collaborators of Yuejun Fu. A scholar is included among the top collaborators of Yuejun Fu 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 Yuejun Fu. Yuejun Fu 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.
Wang, Chen, et al.. (2025). miR-34-5p, a potential RNA biopesticide for controlling Spodoptera frugiperda by targeting of SfEcR and SfE74. Pesticide Biochemistry and Physiology. 208. 106287–106287.
2.
Wang, Chen, et al.. (2025). Baculovirus dual-phase infection strategy and biotechnological applications: A structural and regulatory review. Biotechnology Advances. 83. 108627–108627.
3.
Liu, Xiaoyan, et al.. (2025). Evolutionary origin of the frameshift sites in the ribosomal frameshifting genes of Euplotes. BMC Genomics. 26(1). 676–676.
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Zhang, Yingying, Yaru Wang, Lingling Wang, et al.. (2024). Cep131-Cep162 and Cby-Fam92 complexes cooperatively maintain Cep290 at the basal body and contribute to ciliogenesis initiation. PLoS Biology. 22(3). e3002330–e3002330. 3 indexed citations
7.
Wu, Jiangtao, et al.. (2023). Enhanced in vivo antitumor efficacy through the nanodiamond mediated co-delivery of drugs. Journal of Drug Delivery Science and Technology. 88. 104984–104984. 7 indexed citations
8.
Li, Jia, et al.. (2023). eIF5A promotes +1 programmed ribosomal frameshifting in Euplotes octocarinatus. International Journal of Biological Macromolecules. 254(Pt 1). 127743–127743. 3 indexed citations
9.
Hu, Bo, et al.. (2023). pH-Sensitive nanodiamond co-delivery of retinal and doxorubicin boosts breast cancer chemotherapy. RSC Advances. 13(39). 27403–27414. 5 indexed citations
10.
Fu, Yuejun, Ling Huang, Hao Tang, & Ruoyu Huang. (2020). hsa_circRNA_012515 Is Highly Expressed in NSCLC Patients and Affects Its Prognosis. SHILAP Revista de lepidopterología. 1 indexed citations
11.
Jiang, Yuanyuan, Yuejun Fu, Zhiwei Ren, Huiyang Gou, & Chenggang Xu. (2020). Screening and application of inducible promoters in Ruminiclostridium papyrosolvens. Letters in Applied Microbiology. 71(4). 428–436. 4 indexed citations
12.
Zheng, Shuhua & Yuejun Fu. (2020). Age-related copy number variations and expression levels of F-box protein FBXL20 predict ovarian cancer prognosis. Translational Oncology. 13(12). 100863–100863. 7 indexed citations
13.
Fu, Yuejun, Shuhua Zheng, Yali Zheng, et al.. (2012). Glioma derived isocitrate dehydrogenase-2 mutations induced up-regulation of HIF-1α and β-catenin signaling: Possible impact on glioma cell metastasis and chemo-resistance. The International Journal of Biochemistry & Cell Biology. 44(5). 770–775. 39 indexed citations
14.
Yuan, Tian, et al.. (2012). Cloning, characterization and expression of the LECT2 gene in grass carp. Fish Physiology and Biochemistry. 39(4). 829–835. 7 indexed citations
15.
Yin, Litian, Yuejun Fu, & Aihua Liang. (2009). Heterologous expression of chloride ion channel toxin BmK CTa from Buthus martensii Karsch in E. coli and its inhibitory effect on proliferation of host bacterial strain.. Zhongguo shengwuzhipinxue zazhi. 22(3). 209–212. 1 indexed citations
16.
Tian, Guo‐Bao, Hongning Wang, Likou Zou, et al.. (2009). Detection of CTX-M-15, CTX-M-22, and SHV-2 Extended-Spectrum β-Lactamases (ESBLs) in Escherichia coli Fecal-Sample Isolates from Pig Farms in China. Foodborne Pathogens and Disease. 6(3). 297–304. 50 indexed citations
17.
Xu, Chenggang, Xiaojun Fan, Yuejun Fu, & Aihua Liang. (2008). Effect of location of the His-tag on the production of soluble and functional Buthus martensii Karsch insect toxin. Protein Expression and Purification. 59(1). 103–109. 30 indexed citations
18.
Fu, Yuejun, Litian Yin, Chaofeng Zhang, et al.. (2006). Therapeutic potential of chlorotoxin-like neurotoxin from the Chinese scorpion for human gliomas. Neuroscience Letters. 412(1). 62–67. 61 indexed citations
19.
Fu, Yuejun, Baofeng Chai, Wei Wang, et al.. (2004). Expression and purification of the BmK Mm2 neurotoxin from the scorpion Buthus martensii Karsch and its biological activity test. Protein Expression and Purification. 38(1). 45–50. 10 indexed citations
20.
Hao, Xiang‐Rong, Yuejun Fu, Hong Jin, & T Liu. (2001). Calcium-activated potassium current in single Novikoff cell. Methods and Findings in Experimental and Clinical Pharmacology. 23(2). 55–55. 1 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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