Ning Shi

64 total papers · 874 total citations
46 papers, 568 citations indexed

About

Ning Shi is a scholar working on Infectious Diseases, Molecular Biology and Animal Science and Zoology. According to data from OpenAlex, Ning Shi has authored 46 papers receiving a total of 568 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Infectious Diseases, 16 papers in Molecular Biology and 10 papers in Animal Science and Zoology. Recurrent topics in Ning Shi's work include Virus-based gene therapy research (10 papers), Animal Virus Infections Studies (10 papers) and Viral Infections and Vectors (9 papers). Ning Shi is often cited by papers focused on Virus-based gene therapy research (10 papers), Animal Virus Infections Studies (10 papers) and Viral Infections and Vectors (9 papers). Ning Shi collaborates with scholars based in China, United States and Germany. Ning Shi's co-authors include Ming Duan, Maolin Zhang, Zhenhong Guan, Ningyi Jin, Xijun Yan, Bo Hu, Lixia Li, Huijun Lu, Xue Bai and Wenjing Feng and has published in prestigious journals such as Journal of Virology, Biochemical and Biophysical Research Communications and Frontiers in Microbiology.

In The Last Decade

Ning Shi

42 papers receiving 551 citations

Author Peers

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

Author Last Decade Papers Cites
Ning Shi 187 147 141 132 127 46 568
Minhua Sun 203 1.1× 159 1.1× 168 1.2× 121 0.9× 227 1.8× 40 573
Ching‐Dong Chang 180 1.0× 186 1.3× 134 1.0× 109 0.8× 133 1.0× 40 565
Enqi Du 197 1.1× 264 1.8× 127 0.9× 126 1.0× 175 1.4× 48 668
Huaichang Sun 292 1.6× 199 1.4× 83 0.6× 194 1.5× 212 1.7× 64 690
Jessika‐M. V. Cavalleri 203 1.1× 120 0.8× 167 1.2× 101 0.8× 183 1.4× 57 691
Bo Ni 190 1.0× 125 0.9× 139 1.0× 110 0.8× 190 1.5× 37 648
Shaohua Hou 262 1.4× 239 1.6× 103 0.7× 162 1.2× 174 1.4× 40 684
Boli Hu 172 0.9× 244 1.7× 320 2.3× 65 0.5× 56 0.4× 33 656
Hongchao Gou 180 1.0× 250 1.7× 189 1.3× 78 0.6× 107 0.8× 39 631
Zhaocai Li 167 0.9× 159 1.1× 128 0.9× 94 0.7× 164 1.3× 40 581

Countries citing papers authored by Ning Shi

Since Specialization
Citations

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

Fields of papers citing papers by Ning Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ning Shi

This figure shows the co-authorship network connecting the top 25 collaborators of Ning Shi. A scholar is included among the top collaborators of Ning Shi 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 Ning Shi. Ning Shi 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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2026