Pengpeng Jin

27 total papers · 658 total citations
17 papers, 533 citations indexed

About

Pengpeng Jin is a scholar working on Molecular Biology, Neurology and Immunology. According to data from OpenAlex, Pengpeng Jin has authored 17 papers receiving a total of 533 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 3 papers in Neurology and 3 papers in Immunology. Recurrent topics in Pengpeng Jin's work include Neuroinflammation and Neurodegeneration Mechanisms (3 papers), Neurological Disease Mechanisms and Treatments (3 papers) and Pharmacological Effects of Natural Compounds (2 papers). Pengpeng Jin is often cited by papers focused on Neuroinflammation and Neurodegeneration Mechanisms (3 papers), Neurological Disease Mechanisms and Treatments (3 papers) and Pharmacological Effects of Natural Compounds (2 papers). Pengpeng Jin collaborates with scholars based in China, Japan and Hong Kong. Pengpeng Jin's co-authors include Shuangxing Hou, Ying Wang, Li Xu, Liping Han, Yanchun Deng, Na Qin, Zhongliang Wu, Changyou Zhan, Weiyue Lu and Juan Guan and has published in prestigious journals such as ACS Nano, PLoS ONE and Endocrinology.

In The Last Decade

Pengpeng Jin

16 papers receiving 525 citations

Author Peers

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

Author Last Decade Papers Cites
Pengpeng Jin 219 112 76 68 62 17 533
Ji Wang 188 0.9× 150 1.3× 26 0.3× 26 0.4× 67 1.1× 29 569
Yogeshwar Shukla 153 0.7× 193 1.7× 33 0.4× 34 0.5× 29 0.5× 15 616
Matthew Honeggar 204 0.9× 81 0.7× 42 0.6× 40 0.6× 67 1.1× 15 566
Jiajia Ji 187 0.9× 116 1.0× 15 0.2× 48 0.7× 80 1.3× 40 520
Laura Botto 229 1.0× 111 1.0× 85 1.1× 11 0.2× 33 0.5× 34 567
Meng Yang 103 0.5× 273 2.4× 24 0.3× 42 0.6× 134 2.2× 15 612
Yang Dan 251 1.1× 74 0.7× 19 0.3× 52 0.8× 45 0.7× 16 566
Ying Shen 222 1.0× 134 1.2× 24 0.3× 35 0.5× 82 1.3× 33 593
Xuetao Wei 184 0.8× 127 1.1× 44 0.6× 25 0.4× 71 1.1× 44 547
Pengjuan Xu 226 1.0× 39 0.3× 53 0.7× 36 0.5× 52 0.8× 25 577

Countries citing papers authored by Pengpeng Jin

Since Specialization
Citations

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

Fields of papers citing papers by Pengpeng Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pengpeng Jin

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