Zhangyi Qu

42 total papers · 698 total citations
25 papers, 541 citations indexed

About

Zhangyi Qu is a scholar working on Molecular Biology, Genetics and Infectious Diseases. According to data from OpenAlex, Zhangyi Qu has authored 25 papers receiving a total of 541 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 8 papers in Genetics and 6 papers in Infectious Diseases. Recurrent topics in Zhangyi Qu's work include Virus-based gene therapy research (8 papers), Viral Infectious Diseases and Gene Expression in Insects (6 papers) and Influenza Virus Research Studies (3 papers). Zhangyi Qu is often cited by papers focused on Virus-based gene therapy research (8 papers), Viral Infectious Diseases and Gene Expression in Insects (6 papers) and Influenza Virus Research Studies (3 papers). Zhangyi Qu collaborates with scholars based in China, United Kingdom and Czechia. Zhangyi Qu's co-authors include Yingchen Wang, Lei Shang, Lijuan Zhang, Xiaohui Yuan, Xiaotong Wang, Shen Jiang, Yang Li, Hong Gao, Shuqiu Wang and Yunpeng Wang and has published in prestigious journals such as PLoS ONE, Analytical Chemistry and Chemical Engineering Journal.

In The Last Decade

Zhangyi Qu

24 papers receiving 522 citations

Author Peers

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

Author						Papers	Cites
Zhangyi Qu	245	155	65	63	58	25	541
Zhijun Xiao	178 0.7×	101 0.7×	14 0.2×	52 0.8×	75 1.3×	37	514
Renu Garg	197 0.8×	98 0.6×	156 2.4×	21 0.3×	11 0.2×	29	610
Diletta Scaccabarozzi	156 0.6×	72 0.5×	12 0.2×	14 0.2×	59 1.0×	17	603
Shiyuan Wen	213 0.9×	145 0.9×	79 1.2×	25 0.4×	38 0.7×	33	518
Miguel Aroso	191 0.8×	91 0.6×	84 1.3×	27 0.4×	27 0.5×	25	489
Srabanti Rakshit	166 0.7×	112 0.7×	10 0.2×	25 0.4×	12 0.2×	21	545
Yan Quan Lee	200 0.8×	52 0.3×	37 0.6×	21 0.3×	14 0.2×	11	562
Dan Shen	229 0.9×	83 0.5×	18 0.3×	42 0.7×	69 1.2×	26	612
Jane A. Fagerland	170 0.7×	154 1.0×	15 0.2×	68 1.1×	12 0.2×	31	614
Yan Su	115 0.5×	86 0.6×	194 3.0×	9 0.1×	31 0.5×	21	514

Countries citing papers authored by Zhangyi Qu

Since Specialization

Citations

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

Fields of papers citing papers by Zhangyi Qu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhangyi Qu

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

All Works

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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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