Jing Jin

106 total papers · 3.6k total citations
65 papers, 2.3k citations indexed

About

Jing Jin is a scholar working on Epidemiology, Immunology and Virology. According to data from OpenAlex, Jing Jin has authored 65 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Epidemiology, 20 papers in Immunology and 18 papers in Virology. Recurrent topics in Jing Jin's work include HIV Research and Treatment (16 papers), Influenza Virus Research Studies (12 papers) and Virus-based gene therapy research (8 papers). Jing Jin is often cited by papers focused on HIV Research and Treatment (16 papers), Influenza Virus Research Studies (12 papers) and Virus-based gene therapy research (8 papers). Jing Jin collaborates with scholars based in United States, China and United Kingdom. Jing Jin's co-authors include Walther Mothes, Nathan M. Sherer, Peng Zhong, Ronald C. Montelaro, Graham Simmons, Pradeep D. Uchil, David E. Ott, Robin Chan, Markus R. Wenk and Guanghou Shui and has published in prestigious journals such as Nature, New England Journal of Medicine and Cell.

In The Last Decade

Jing Jin

63 papers receiving 2.2k citations

Hit Papers

Nirsevimab for Prevention... 2023 2026 2024 2023 50 100 150

Author Peers

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

Author Last Decade Papers Cites
Jing Jin 819 676 622 554 495 65 2.3k
Zehava Grossman 520 0.6× 731 1.1× 1.3k 2.0× 794 1.4× 361 0.7× 75 2.6k
Luis M. Schang 1.3k 1.6× 803 1.2× 321 0.5× 300 0.5× 203 0.4× 70 2.7k
D. J. Hockley 460 0.6× 610 0.9× 737 1.2× 855 1.5× 282 0.6× 65 3.0k
Jean‐Marc Crance 585 0.7× 480 0.7× 1.0k 1.6× 470 0.8× 701 1.4× 68 2.1k
Marion C. Lanteri 622 0.8× 464 0.7× 1.3k 2.0× 244 0.4× 1.3k 2.5× 84 3.2k
Fredrik Vannberg 350 0.4× 868 1.3× 450 0.7× 473 0.9× 186 0.4× 43 2.2k
Friedrich Dorner 587 0.7× 813 1.2× 536 0.9× 638 1.2× 179 0.4× 115 3.0k
Richard J. Sugrue 1.5k 1.9× 895 1.3× 870 1.4× 197 0.4× 407 0.8× 74 2.6k
Arianna Calistri 846 1.0× 1.1k 1.7× 855 1.4× 807 1.5× 316 0.6× 81 2.9k
Nathaniel J. Moorman 1.6k 1.9× 1.3k 1.9× 626 1.0× 195 0.4× 248 0.5× 90 3.3k

Countries citing papers authored by Jing Jin

Since Specialization
Citations

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

Fields of papers citing papers by Jing Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jing Jin

This figure shows the co-authorship network connecting the top 25 collaborators of Jing Jin. A scholar is included among the top collaborators of Jing Jin 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 Jing Jin. Jing Jin 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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