Guiqing Peng

4.1k total citations
78 papers, 2.9k citations indexed

About

Guiqing Peng is a scholar working on Infectious Diseases, Animal Science and Zoology and Genetics. According to data from OpenAlex, Guiqing Peng has authored 78 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 57 papers in Infectious Diseases, 50 papers in Animal Science and Zoology and 23 papers in Genetics. Recurrent topics in Guiqing Peng's work include Animal Virus Infections Studies (50 papers), Viral gastroenteritis research and epidemiology (40 papers) and SARS-CoV-2 and COVID-19 Research (26 papers). Guiqing Peng is often cited by papers focused on Animal Virus Infections Studies (50 papers), Viral gastroenteritis research and epidemiology (40 papers) and SARS-CoV-2 and COVID-19 Research (26 papers). Guiqing Peng collaborates with scholars based in China, United States and Canada. Guiqing Peng's co-authors include Fang Li, Shaobo Xiao, Kailang Wu, Liurong Fang, Dang Wang, Weikai Li, Zhen F. Fu, Yi-Lun Lin, Huanchun Chen and Robert J. Geraghty and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Guiqing Peng

74 papers receiving 2.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Guiqing Peng China 30 2.1k 1.5k 744 510 325 78 2.9k
Peter J. Bredenbeek Netherlands 29 2.8k 1.3× 1.4k 0.9× 465 0.6× 1.0k 2.0× 455 1.4× 49 4.3k
Monique H. Verheije Netherlands 31 1.8k 0.9× 1.2k 0.8× 437 0.6× 674 1.3× 356 1.1× 62 3.1k
Yan‐Dong Tang China 26 1.3k 0.6× 935 0.6× 638 0.9× 452 0.9× 305 0.9× 84 2.3k
Sonia Zúñiga Spain 24 2.1k 1.0× 1.3k 0.8× 365 0.5× 707 1.4× 250 0.8× 47 2.7k
Fernando Almazán Spain 34 2.6k 1.2× 1.5k 1.0× 511 0.7× 1.0k 2.0× 332 1.0× 68 4.2k
Stanley G. Sawicki United States 33 2.6k 1.2× 1.4k 0.9× 403 0.5× 897 1.8× 319 1.0× 54 3.8k
Tom Gallagher United States 27 2.3k 1.1× 992 0.6× 372 0.5× 662 1.3× 375 1.2× 47 3.2k
Kumari G. Lokugamage United States 23 2.7k 1.3× 759 0.5× 177 0.2× 822 1.6× 524 1.6× 35 3.3k
Marjolein Kikkert Netherlands 36 2.6k 1.2× 1.0k 0.7× 666 0.9× 1.9k 3.6× 1.1k 3.5× 69 5.7k
David A. Brian United States 34 2.9k 1.3× 2.6k 1.7× 751 1.0× 532 1.0× 134 0.4× 74 3.5k

Countries citing papers authored by Guiqing Peng

Since Specialization
Citations

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

Fields of papers citing papers by Guiqing Peng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Guiqing Peng

This figure shows the co-authorship network connecting the top 25 collaborators of Guiqing Peng. A scholar is included among the top collaborators of Guiqing Peng 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 Guiqing Peng. Guiqing Peng 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.
Yang, Yuan, Xiumei Meng, Zhenyu Zhang, et al.. (2025). Engineering a TGEV S-trimer chimera with PEDV D0-NTD generates potent neutralizing antibodies against both viruses. Journal of Virology. 99(11). e0145225–e0145225.
2.
Zhou, Yanrong, Peng Sun, Zhixiang Yang, et al.. (2024). The S2 Pocket Governs the Genus‐Specific Substrate Selectivity of Coronavirus 3C‐Like Protease. Advanced Science. 11(44). e2407766–e2407766. 3 indexed citations
3.
Shi, Yuejun, et al.. (2024). Analytical insights, modulation and compositional dynamics of the feline gut microbiota: a review. SHILAP Revista de lepidopterología. 4(1).
4.
Han, Yang, et al.. (2024). Crystal structure of the ATPase domain of porcine circovirus type 2 Rep protein. Journal of General Virology. 105(3).
5.
Liang, Rui, Yanan Fu, Zhou Shen, et al.. (2024). EP152R ‐mediated endoplasmic reticulum stress contributes to African swine fever virus infection via the PERK ‐ eIF2α pathway. The FASEB Journal. 38(22). e70187–e70187. 3 indexed citations
6.
Cao, Hua, Mengjia Zhang, Dongfan Li, et al.. (2024). A porcine kidney-derived clonal cell line with clear genetic annotation is highly susceptible to African swine fever virus. Veterinary Research. 55(1). 42–42. 3 indexed citations
7.
Chen, Jiyao, Peng Sun, Gang Ye, et al.. (2024). Structural Basis for the Acylation Reaction of Alphacoronavirus 3C-like Protease. ACS Catalysis. 14(11). 8330–8342. 1 indexed citations
8.
Liu, Zirui, Rui Liang, Yuanyuan Yan, et al.. (2024). Novel mutation N588 residue in the NS1 protein of feline parvovirus greatly augments viral replication. Journal of Virology. 98(5). e0009324–e0009324. 1 indexed citations
9.
Wang, Xueying, et al.. (2023). Innate immune escape and adaptive immune evasion of African swine fever virus: A review. Virology. 587. 109878–109878. 15 indexed citations
10.
Fu, Yanan, et al.. (2023). DYRK1A is a multifunctional host factor that regulates coronavirus replication in a kinase-independent manner. Journal of Virology. 98(1). e0123923–e0123923. 3 indexed citations
11.
Zou, Jiahui, Kelu Yang, Guiqing Peng, et al.. (2022). Identification of a small compound that specifically inhibits Zika virus in vitro and in vivo by targeting the NS2B-NS3 protease. Antiviral Research. 199. 105255–105255. 8 indexed citations
12.
Zhao, Changzhi, Zhen F. Fu, Yanan Fu, et al.. (2021). Genome-scale CRISPR screen identifies TMEM41B as a multi-function host factor required for coronavirus replication. PLoS Pathogens. 17(12). e1010113–e1010113. 43 indexed citations
13.
14.
Liu, Jiajia, Bingrong Xu, Lili Niu, et al.. (2020). Application of CRISPR-Cas12a Enhanced Fluorescence Assay Coupled with Nucleic Acid Amplification for the Sensitive Detection of African Swine Fever Virus. ACS Synthetic Biology. 9(9). 2339–2350. 63 indexed citations
15.
Shang, Jian, Yushun Wan, Chang Liu, et al.. (2020). Structure of mouse coronavirus spike protein complexed with receptor reveals mechanism for viral entry. PLoS Pathogens. 16(3). e1008392–e1008392. 105 indexed citations
16.
Peng, Qi, Liurong Fang, Zhen Ding, et al.. (2019). Rapid manipulation of the porcine epidemic diarrhea virus genome by CRISPR/Cas9 technology. Journal of Virological Methods. 276. 113772–113772. 33 indexed citations
17.
Fang, Puxian, Qi Peng, Jie Ren, et al.. (2019). Porcine deltacoronavirus nucleocapsid protein antagonizes IFN-β production by impairing dsRNA and PACT binding to RIG-I. Virus Genes. 55(4). 520–531. 33 indexed citations
18.
19.
Ye, Gang, Feng Deng, Zhou Shen, et al.. (2016). Structural basis for the dimerization and substrate recognition specificity of porcine epidemic diarrhea virus 3C-like protease. Virology. 494. 225–235. 45 indexed citations
20.
Li, Youwen, Yuejun Shi, Feng Deng, et al.. (2015). Rabies virus phosphoprotein interacts with ribosomal protein L9 and affects rabies virus replication. Virology. 488. 216–224. 34 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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