Kuang‐Yu Chen

831 total citations
10 papers, 103 citations indexed

About

Kuang‐Yu Chen is a scholar working on Molecular Biology, Epidemiology and Computational Theory and Mathematics. According to data from OpenAlex, Kuang‐Yu Chen has authored 10 papers receiving a total of 103 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 3 papers in Epidemiology and 3 papers in Computational Theory and Mathematics. Recurrent topics in Kuang‐Yu Chen's work include Influenza Virus Research Studies (3 papers), Computational Drug Discovery Methods (3 papers) and Synthesis and biological activity (2 papers). Kuang‐Yu Chen is often cited by papers focused on Influenza Virus Research Studies (3 papers), Computational Drug Discovery Methods (3 papers) and Synthesis and biological activity (2 papers). Kuang‐Yu Chen collaborates with scholars based in Taiwan, France and United States. Kuang‐Yu Chen's co-authors include Nadia Naffakh, Catherine Isel, Chu‐Ren Huang, Fengyi Chen, Keh-Jiann Chen, Vincent Enouf, Adrien Delpal, Étienne Decroly, Fabrice Agou and David Courtney and has published in prestigious journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Kuang‐Yu Chen

9 papers receiving 99 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Kuang‐Yu Chen Taiwan	5	32	31	28	24	17	10	103
Kent Shefchek United States	6	36 1.1×	18 0.6×	81 2.9×	8 0.3×	12 0.7×	9	163
Ante Karoglan Germany	4	59 1.8×	38 1.2×	24 0.9×	9 0.4×	12 0.7×	8	187
Xinru Qiu United States	7	4 0.1×	13 0.4×	39 1.4×	12 0.5×	6 0.4×	23	125
Michael Horwath United States	6	7 0.2×	78 2.5×	45 1.6×	25 1.0×	63 3.7×	12	178
Derek Reiman United States	9	35 1.1×	12 0.4×	179 6.4×	22 0.9×	8 0.5×	17	251
Yuxuan Pang China	8	7 0.2×	36 1.2×	213 7.6×	13 0.5×	12 0.7×	17	257
Aaron McGeever United States	6	8 0.3×	30 1.0×	55 2.0×	14 0.6×	13 0.8×	10	109
Mardiana Marzuki Singapore	4	3 0.1×	56 1.8×	57 2.0×	21 0.9×	61 3.6×	5	132
Magali Berland France	9	14 0.4×	10 0.3×	153 5.5×	13 0.5×	16 0.9×	13	216
Jean-Jacques Codani France	5	24 0.8×	8 0.3×	148 5.3×	8 0.3×	7 0.4×	6	169

Countries citing papers authored by Kuang‐Yu Chen

Since Specialization

Citations

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

Fields of papers citing papers by Kuang‐Yu Chen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kuang‐Yu 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 Kuang‐Yu Chen. The network helps show where Kuang‐Yu Chen may publish in the future.

Co-authorship network of co-authors of Kuang‐Yu Chen

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

All Works

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10 of 10 papers shown

Paisant, Sylvain, Kuang‐Yu Chen, Laurence Thirion, et al.. (2025). Noncovalent Inhibitors of SARS-CoV-2 Main Protease: A Rescaffolding Attempt. Synthesis. 57(9). 1627–1634.

Chen, Li‐Han, Kuang‐Yu Chen, Kung‐Ta Lee, et al.. (2024). Single-strain probiotics enhance growth, anti-pathogen immunity, and resistance to Nocardia seriolae in grey mullet (Mugil cephalus) via gut microbiota modulation. SHILAP Revista de lepidopterología. 6(1). 67–67. 6 indexed citations

Chen, Kuang‐Yu, Mary B. O’Neill, Mathieu Bahin, et al.. (2023). High-throughput droplet-based analysis of influenza A virus genetic reassortment by single-virus RNA sequencing. Proceedings of the National Academy of Sciences. 120(6). e2211098120–e2211098120. 8 indexed citations

Chen, Kuang‐Yu, Adrien Delpal, Étienne Decroly, et al.. (2023). Design and synthesis of naturally-inspired SARS-CoV-2 inhibitors. RSC Medicinal Chemistry. 14(3). 507–519. 4 indexed citations

Chiou, Tsyr-Huei, Hongjie Zhang, How‐Ran Chao, et al.. (2023). Persistent Halogenated Organic Pollutants in Deep-Water-Deposited Particulates from South China Sea. Toxics. 11(12). 968–968. 2 indexed citations

Chen, Kuang‐Yu, Sylvain Paisant, Agnès Zettor, et al.. (2022). A highly sensitive cell-based luciferase assay for high-throughput automated screening of SARS-CoV-2 nsp5/3CLpro inhibitors. Antiviral Research. 201. 105272–105272. 21 indexed citations

Liu, Liyu, et al.. (2021). Color-complexity enabled exhaustive color-dots identification and spatial patterns testing in images. PLoS ONE. 16(5). e0251258–e0251258. 1 indexed citations

Chen, Kuang‐Yu, et al.. (2019). Influenza virus polymerase subunits co-evolve to ensure proper levels of dimerization of the heterotrimer. PLoS Pathogens. 15(10). e1008034–e1008034. 26 indexed citations

Chen, Kuang‐Yu, et al.. (2019). Novel application ofInfluenza A virus-inoculated chorioallantoic membrane to characterize a NP-specific monoclonal antibody for immunohistochemistry assaying. Journal of Veterinary Science. 20(1). 51–51. 3 indexed citations

10.

Huang, Chu‐Ren, et al.. (2000). Sinica Treebank. 12. 29–29. 32 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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