Yao-Qing Chen

3.2k total citations
53 papers, 1.2k citations indexed

About

Yao-Qing Chen is a scholar working on Infectious Diseases, Epidemiology and Molecular Biology. According to data from OpenAlex, Yao-Qing Chen has authored 53 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Infectious Diseases, 18 papers in Epidemiology and 15 papers in Molecular Biology. Recurrent topics in Yao-Qing Chen's work include SARS-CoV-2 and COVID-19 Research (14 papers), Influenza Virus Research Studies (9 papers) and COVID-19 Clinical Research Studies (8 papers). Yao-Qing Chen is often cited by papers focused on SARS-CoV-2 and COVID-19 Research (14 papers), Influenza Virus Research Studies (9 papers) and COVID-19 Clinical Research Studies (8 papers). Yao-Qing Chen collaborates with scholars based in China, United States and Hong Kong. Yao-Qing Chen's co-authors include Jingyi Yang, Huimin Yan, Dihan Zhou, Qiaoli Li, Chengsong Ye, Xin Yu, Longfei Shu, Peng Wang, Liping Wang and Lizheng Guo and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and The Journal of Experimental Medicine.

In The Last Decade

Yao-Qing Chen

48 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yao-Qing Chen China 17 536 312 288 261 187 53 1.2k
Thierry Morin France 23 487 0.9× 166 0.5× 207 0.7× 372 1.4× 205 1.1× 61 1.5k
Lifang Jiang China 22 504 0.9× 358 1.1× 246 0.9× 236 0.9× 38 0.2× 89 1.6k
Yi‐Han Lin United States 15 339 0.6× 685 2.2× 127 0.4× 111 0.4× 49 0.3× 40 1.3k
Toshihiro Ito Japan 22 447 0.8× 253 0.8× 762 2.6× 175 0.7× 152 0.8× 68 1.7k
Baoming Liu United States 24 417 0.8× 301 1.0× 578 2.0× 355 1.4× 43 0.2× 37 1.4k
Michele Muscillo Italy 28 1.2k 2.2× 162 0.5× 299 1.0× 45 0.2× 279 1.5× 68 1.8k
Åsa Sjöling Sweden 30 547 1.0× 658 2.1× 160 0.6× 740 2.8× 24 0.1× 91 2.7k
Julia A. Tree United Kingdom 14 464 0.9× 253 0.8× 344 1.2× 130 0.5× 41 0.2× 24 895
Téngfēi Zhāng China 24 309 0.6× 382 1.2× 151 0.5× 236 0.9× 139 0.7× 69 1.5k
Haitao Ding United States 20 321 0.6× 362 1.2× 265 0.9× 445 1.7× 20 0.1× 50 1.5k

Countries citing papers authored by Yao-Qing Chen

Since Specialization
Citations

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

Fields of papers citing papers by Yao-Qing Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yao-Qing Chen. 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 Yao-Qing Chen. The network helps show where Yao-Qing Chen may publish in the future.

Co-authorship network of co-authors of Yao-Qing Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Yao-Qing Chen. A scholar is included among the top collaborators of Yao-Qing Chen 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 Yao-Qing Chen. Yao-Qing Chen 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, Wenhao, Rui Li, Weiyi Huang, et al.. (2025). RNF138 regulates skeletal muscle differentiation via the Wnt/β-catenin signaling pathway. Theranostics. 15(10). 4446–4464.
2.
Zheng, Lifeng, Chao Lan, An Zhu, et al.. (2025). Landscape analysis of m6A modification reveals the dysfunction of bone metabolism in osteoporosis mice. Heliyon. 11(3). e42123–e42123.
3.
Yan, Jiangyu, Lin Liu, Yao-Qing Chen, et al.. (2024). G-quadruplexes on chromosomal DNA negatively regulates topoisomerase 1 activity. Nucleic Acids Research. 52(5). 2142–2156. 7 indexed citations
4.
Chen, Junbo, Yibing Cheng, Yao-Qing Chen, et al.. (2023). Antibody signatures in hospitalized hand, foot and mouth disease patients with acute enterovirus A71 infection. PLoS Pathogens. 19(6). e1011420–e1011420. 5 indexed citations
5.
6.
Yang, Jingyi, Meiqin Liu, Lin Liu, et al.. (2022). A triple-RBD-based mucosal vaccine provides broad protection against SARS-CoV-2 variants of concern. Cellular and Molecular Immunology. 19(11). 1279–1289. 22 indexed citations
7.
Li, Minchao, Yajie Liu, Jin Zhao, et al.. (2022). Rational design of AAVrh10-vectored ACE2 functional domain to broadly block the cell entry of SARS-CoV-2 variants. Antiviral Research. 205. 105383–105383. 9 indexed citations
8.
Chen, Liqian, Zhang Zhang, Hong-Xuan Chen, et al.. (2022). High-precision mapping reveals rare N6-deoxyadenosine methylation in the mammalian genome. Cell Discovery. 8(1). 138–138. 7 indexed citations
9.
Yang, Jingyi, Maohua Zhong, Ejuan Zhang, et al.. (2021). Broad phenotypic alterations and potential dysfunction of lymphocytes in individuals clinically recovered from COVID-19. Journal of Molecular Cell Biology. 13(3). 197–209. 21 indexed citations
10.
Zhong, Maohua, Qingyu Yang, Ke Hong, et al.. (2021). Alterations in Phenotypes and Responses of T Cells Within 6 Months of Recovery from COVID-19: A Cohort Study. Virologica Sinica. 36(5). 859–868. 14 indexed citations
11.
Wang, Yaqi, Guoqin Mai, Min Zou, et al.. (2021). Heavy chain sequence-based classifier for the specificity of human antibodies. Briefings in Bioinformatics. 23(1). 3 indexed citations
12.
Wang, Liping, Chengsong Ye, Lizheng Guo, et al.. (2021). Assessment of the UV/Chlorine Process in the Disinfection of Pseudomonas aeruginosa: Efficiency and Mechanism. Environmental Science & Technology. 55(13). 9221–9230. 158 indexed citations
13.
Chen, Xiaoping, Mengxin Xu, Yanling Li, et al.. (2021). Research on Influencing Factors and Classification of Patients With Mild and Severe COVID-19 Symptoms. Frontiers in Cellular and Infection Microbiology. 11. 670823–670823. 1 indexed citations
14.
Zhang, Chi, Yi Teng, Ting Xie, et al.. (2020). Impact of Systematic Factors on the Outbreak Outcomes of the Novel COVID-19 Disease in China: Factor Analysis Study. Journal of Medical Internet Research. 22(11). e23853–e23853. 11 indexed citations
15.
Dugan, Haley L., Jenna J. Guthmiller, Philip Arevalo, et al.. (2020). Preexisting immunity shapes distinct antibody landscapes after influenza virus infection and vaccination in humans. Science Translational Medicine. 12(573). 72 indexed citations
16.
17.
Henry, Carole, Anna-Karin E. Palm, Henry A. Utset, et al.. (2019). Monoclonal Antibody Responses after Recombinant Hemagglutinin Vaccine versus Subunit Inactivated Influenza Virus Vaccine: a Comparative Study. Journal of Virology. 93(21). 18 indexed citations
18.
Yang, Jingyi, Ejuan Zhang, Fang Liu, et al.. (2013). Flagellins of <b><i>Salmonella</i></b> Typhi and Nonpathogenic <b><i>Escherichia coli</i></b> Are Differentially Recognized through the NLRC4 Pathway in Macrophages. Journal of Innate Immunity. 6(1). 47–57. 34 indexed citations
19.
Chen, Yao-Qing, Luyang Cao, Maohua Zhong, et al.. (2012). Anti-HIV-1 Activity of a New Scorpion Venom Peptide Derivative Kn2-7. PLoS ONE. 7(4). e34947–e34947. 65 indexed citations
20.
Li, Qiaoli, Zhenhuan Zhao, Dihan Zhou, et al.. (2011). Virucidal activity of a scorpion venom peptide variant mucroporin-M1 against measles, SARS-CoV and influenza H5N1 viruses. Peptides. 32(7). 1518–1525. 117 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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