Qingjun Wu

10.7k total citations · 1 hit paper
229 papers, 6.7k citations indexed

About

Qingjun Wu is a scholar working on Insect Science, Plant Science and Molecular Biology. According to data from OpenAlex, Qingjun Wu has authored 229 papers receiving a total of 6.7k indexed citations (citations by other indexed papers that have themselves been cited), including 168 papers in Insect Science, 109 papers in Plant Science and 98 papers in Molecular Biology. Recurrent topics in Qingjun Wu's work include Insect-Plant Interactions and Control (142 papers), Insect Resistance and Genetics (83 papers) and Insect and Pesticide Research (69 papers). Qingjun Wu is often cited by papers focused on Insect-Plant Interactions and Control (142 papers), Insect Resistance and Genetics (83 papers) and Insect and Pesticide Research (69 papers). Qingjun Wu collaborates with scholars based in China, United States and United Kingdom. Qingjun Wu's co-authors include Youjun Zhang, Shaoli Wang, Wen Xie, Xuguo Zhou, Baoyun Xu, Huipeng Pan, Zhaojiang Guo, Xin Yang, Qi Su and Baiming Liu and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Qingjun Wu

217 papers receiving 6.6k citations

Hit Papers

Whitefly hijacks a plant ... 2021 2026 2022 2024 2021 50 100 150

Author Peers

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

Author Last Decade Papers Cites
Qingjun Wu 4.8k 3.3k 3.2k 501 404 229 6.7k
Wen Xie 4.5k 0.9× 3.0k 0.9× 2.7k 0.8× 443 0.9× 377 0.9× 171 5.9k
Xiwu Gao 7.7k 1.6× 4.6k 1.4× 6.2k 1.9× 747 1.5× 701 1.7× 356 10.1k
Chris Bass 6.5k 1.3× 3.7k 1.1× 4.9k 1.5× 1.3k 2.5× 986 2.4× 150 9.2k
Ming‐Guang Feng 6.1k 1.3× 3.1k 0.9× 4.9k 1.5× 232 0.5× 534 1.3× 285 7.9k
Henryk Czosnek 3.8k 0.8× 6.1k 1.8× 1.9k 0.6× 176 0.4× 338 0.8× 142 7.7k
Yu Cheng Zhu 2.7k 0.6× 1.4k 0.4× 2.0k 0.6× 725 1.4× 510 1.3× 137 4.0k
Nemat O. Keyhani 4.2k 0.9× 2.1k 0.6× 3.7k 1.2× 220 0.4× 623 1.5× 165 6.3k
Michael J. Furlong 3.1k 0.6× 2.1k 0.6× 1.9k 0.6× 734 1.5× 358 0.9× 155 4.5k
Chuan‐Xi Zhang 4.0k 0.8× 2.2k 0.7× 3.9k 1.2× 601 1.2× 1.2k 2.9× 337 7.5k
Saskia A. Hogenhout 4.3k 0.9× 7.2k 2.2× 1.9k 0.6× 445 0.9× 282 0.7× 124 8.6k

Countries citing papers authored by Qingjun Wu

Since Specialization
Citations

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

Fields of papers citing papers by Qingjun Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qingjun Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Qingjun Wu. A scholar is included among the top collaborators of Qingjun Wu 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 Qingjun Wu. Qingjun Wu 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.
Luo, Jinque, Ling Wang, Li Zhang, et al.. (2025). Targeting adipocyte differentiation with CRT0066101: activation of AMPK signaling in 3T3-L1 cells. Frontiers in Pharmacology. 16. 1645587–1645587.
2.
Cheng, Gong, Tian Tian, Xin Yang, et al.. (2025). Silencing of the plant‐derived horizontally transferred gene BtSC5DL effectively controls Bemisia tabaci MED . Pest Management Science. 81(6). 2759–2768. 3 indexed citations
4.
Liang, Peng, Yang Zeng, Jie Ning, et al.. (2025). A plant virus manipulates both its host plant and the insect that facilitates its transmission. Science Advances. 11(9). eadr4563–eadr4563. 2 indexed citations
5.
Yang, Fengbo, Tianyu Huang, Tong Zheng Hong, et al.. (2024). Herbivore-induced volatiles reduce the susceptibility of neighboring tomato plants to transmission of a whitefly-borne begomovirus. Journal of Experimental Botany. 75(20). 6663–6675. 3 indexed citations
6.
Wang, Jing, Hongyi Cao, Ying Zhang, et al.. (2024). Identification and analysis of JHBP/TO family genes and their roles in the reproductive fitness cost of resistance in Frankliniella occidentalis (Pergande). Pesticide Biochemistry and Physiology. 204. 106058–106058. 2 indexed citations
7.
Wu, Qingjun, et al.. (2024). High-fidelity prediction of forming quality for self-piercing riveted joints in aluminum alloy based on machine learning. Materials Today Communications. 41. 110319–110319. 3 indexed citations
8.
Wang, Lei, Xinyi Chen, Kai Wang, et al.. (2024). Rickettsia transmission from whitefly to plants benefits herbivore insects but is detrimental to fungal and viral pathogens. mBio. 15(3). e0244823–e0244823. 7 indexed citations
9.
Guo, Zhaojiang, Gong Cheng, Jixing Xia, et al.. (2024). Two horizontally acquired bacterial genes steer the exceptionally efficient and flexible nitrogenous waste cycling in whiteflies. Science Advances. 10(5). eadi3105–eadi3105. 11 indexed citations
10.
Tang, Juan, Haowei Shen, Rong Zhang, et al.. (2023). Seed priming with rutin enhances tomato resistance against the whitefly Bemisia tabaci. Pesticide Biochemistry and Physiology. 194. 105470–105470. 15 indexed citations
11.
Cheng, Gong, Zhaojiang Guo, Yuan Hu, et al.. (2023). A Horizontally Transferred Plant Fatty Acid Desaturase Gene Steers Whitefly Reproduction. Advanced Science. 11(10). e2306653–e2306653. 14 indexed citations
13.
Guo, Zhaojiang, Yang Bai, Le Guo, et al.. (2023). RNA m6A Methylation Suppresses Insect Juvenile Hormone Degradation to Minimize Fitness Costs in Response to A Pathogenic Attack. Advanced Science. 11(6). e2307650–e2307650. 17 indexed citations
14.
Tao, Min, Kun Zhang, Jing Wang, et al.. (2022). Obstructor, a Frankliniella occidentalis protein, promotes transmission of tomato spotted wilt orthotospovirus. Insect Science. 30(3). 741–757. 7 indexed citations
15.
Zhou, X.‐Y., et al.. (2022). The novel HLA‐C*03 allele, HLA‐C*03:597, identified in a Chinese patient. HLA. 100(5). 534–536. 1 indexed citations
16.
Xie, Wen, Buli Fu, Si Xiao, et al.. (2021). Annual analysis of field‐evolved insecticide resistance in Bemisia tabaci across China. Pest Management Science. 77(6). 2990–3001. 28 indexed citations
17.
Guo, Zhaojiang, Shi Kang, Qingjun Wu, et al.. (2021). The regulation landscape of MAPK signaling cascade for thwarting Bacillus thuringiensis infection in an insect host. PLoS Pathogens. 17(9). e1009917–e1009917. 55 indexed citations
18.
Qin, Jianying, Le Guo, Fan Ye, et al.. (2021). MAPK-Activated Transcription Factor PxJun Suppresses PxABCB1 Expression and Confers Resistance to Bacillus thuringiensis Cry1Ac Toxin in Plutella xylostella (L.). Applied and Environmental Microbiology. 87(13). e0046621–e0046621. 24 indexed citations
19.
Fu, Wei, Wen Xie, Zhuo Zhang, et al.. (2013). Exploring Valid Reference Genes for Quantitative Real-time PCR Analysis in Plutella xylostella (Lepidoptera: Plutellidae). International Journal of Biological Sciences. 9(8). 792–802. 151 indexed citations
20.
Li, Rumei, Wen Xie, Shaoli Wang, et al.. (2013). Reference Gene Selection for qRT-PCR Analysis in the Sweetpotato Whitefly, Bemisia tabaci (Hemiptera: Aleyrodidae). PLoS ONE. 8(1). e53006–e53006. 180 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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