Enya Qing

690 total citations
12 papers, 412 citations indexed

About

Enya Qing is a scholar working on Infectious Diseases, Animal Science and Zoology and Immunology. According to data from OpenAlex, Enya Qing has authored 12 papers receiving a total of 412 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Infectious Diseases, 7 papers in Animal Science and Zoology and 3 papers in Immunology. Recurrent topics in Enya Qing's work include SARS-CoV-2 and COVID-19 Research (11 papers), Animal Virus Infections Studies (7 papers) and Viral gastroenteritis research and epidemiology (5 papers). Enya Qing is often cited by papers focused on SARS-CoV-2 and COVID-19 Research (11 papers), Animal Virus Infections Studies (7 papers) and Viral gastroenteritis research and epidemiology (5 papers). Enya Qing collaborates with scholars based in United States, Switzerland and Germany. Enya Qing's co-authors include Tom Gallagher, Michael P. Hantak, Stanley Perlman, Binod Kumar, James T. Earnest, Charlène Raclot, Francisco S. Mesquita, Gijs R. van den Brink, Luciano A. Abriata and Oksana A. Sergeeva and has published in prestigious journals such as Nature Communications, Journal of Virology and Developmental Cell.

In The Last Decade

Enya Qing

12 papers receiving 409 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Enya Qing United States 9 282 151 89 58 45 12 412
Michael P. Hantak United States 8 201 0.7× 149 1.0× 58 0.7× 64 1.1× 47 1.0× 8 373
Lawrence G. Welch United Kingdom 4 240 0.9× 139 0.9× 54 0.6× 48 0.8× 35 0.8× 6 392
Jakub Lupták United Kingdom 6 195 0.7× 141 0.9× 41 0.5× 62 1.1× 35 0.8× 10 512
Kartika Padhan United States 12 291 1.0× 169 1.1× 76 0.9× 184 3.2× 58 1.3× 16 546
Thomas G. Flower United States 7 164 0.6× 222 1.5× 44 0.5× 44 0.8× 79 1.8× 8 419
Azra Lari United States 5 250 0.9× 189 1.3× 45 0.5× 41 0.7× 18 0.4× 8 421
Manuel Hayn Germany 5 406 1.4× 240 1.6× 57 0.6× 134 2.3× 37 0.8× 8 598
Timo Denk Germany 5 405 1.4× 365 2.4× 57 0.6× 131 2.3× 38 0.8× 11 727
Orel Mizrahi Israel 9 380 1.3× 516 3.4× 72 0.8× 133 2.3× 47 1.0× 10 844
Danhua Zhao China 6 186 0.7× 283 1.9× 51 0.6× 94 1.6× 52 1.2× 17 487

Countries citing papers authored by Enya Qing

Since Specialization
Citations

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

Fields of papers citing papers by Enya Qing

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Enya Qing

This figure shows the co-authorship network connecting the top 25 collaborators of Enya Qing. A scholar is included among the top collaborators of Enya Qing 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 Enya Qing. Enya Qing is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

12 of 12 papers shown
1.
Qing, Enya, et al.. (2024). SARS-CoV-2 Omicron variations reveal mechanisms controlling cell entry dynamics and antibody neutralization. PLoS Pathogens. 20(12). e1012757–e1012757. 2 indexed citations
2.
Lei, Ruipeng, Enya Qing, Abby Odle, et al.. (2024). Functional and antigenic characterization of SARS-CoV-2 spike fusion peptide by deep mutational scanning. Nature Communications. 15(1). 4056–4056. 7 indexed citations
3.
Dey, Debajit, Enya Qing, Yanan He, et al.. (2023). A single C-terminal residue controls SARS-CoV-2 spike trafficking and incorporation into VLPs. Nature Communications. 14(1). 8358–8358. 8 indexed citations
4.
Qing, Enya, et al.. (2023). A cell-free platform to measure coronavirus membrane fusion. STAR Protocols. 4(2). 102189–102189. 4 indexed citations
5.
Qing, Enya & Tom Gallagher. (2023). Adaptive variations in SARS-CoV-2 spike proteins: effects on distinct virus-cell entry stages. mBio. 14(4). e0017123–e0017123. 8 indexed citations
6.
Qing, Enya, Pengfei Li, Laura Cooper, et al.. (2022). Inter-domain communication in SARS-CoV-2 spike proteins controls protease-triggered cell entry. Cell Reports. 39(5). 110786–110786. 31 indexed citations
7.
Mesquita, Francisco S., Laurence Abrami, Oksana A. Sergeeva, et al.. (2021). S-acylation controls SARS-CoV-2 membrane lipid organization and enhances infectivity. Developmental Cell. 56(20). 2790–2807.e8. 91 indexed citations
8.
Qing, Enya, et al.. (2021). Dynamics of SARS-CoV-2 Spike Proteins in Cell Entry: Control Elements in the Amino-Terminal Domains. mBio. 12(4). e0159021–e0159021. 47 indexed citations
9.
10.
Qing, Enya, Michael P. Hantak, Stanley Perlman, & Tom Gallagher. (2020). Distinct Roles for Sialoside and Protein Receptors in Coronavirus Infection. mBio. 11(1). 74 indexed citations
11.
Qing, Enya, et al.. (2019). Evaluating MERS-CoV Entry Pathways. Methods in molecular biology. 2099. 9–20. 30 indexed citations
12.
Hantak, Michael P., Enya Qing, James T. Earnest, & Tom Gallagher. (2018). Tetraspanins: Architects of Viral Entry and Exit Platforms. Journal of Virology. 93(6). 56 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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