Mei‐Na Jin

41 total papers · 850 total citations
33 papers, 710 citations indexed

About

Mei‐Na Jin is a scholar working on Molecular Biology, Pharmacology and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Mei‐Na Jin has authored 33 papers receiving a total of 710 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 6 papers in Pharmacology and 5 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Mei‐Na Jin's work include Metabolism, Diabetes, and Cancer (6 papers), Natural Antidiabetic Agents Studies (5 papers) and Cholinesterase and Neurodegenerative Diseases (4 papers). Mei‐Na Jin is often cited by papers focused on Metabolism, Diabetes, and Cancer (6 papers), Natural Antidiabetic Agents Studies (5 papers) and Cholinesterase and Neurodegenerative Diseases (4 papers). Mei‐Na Jin collaborates with scholars based in China, Japan and United States. Mei‐Na Jin's co-authors include Hong‐Quan Duan, Fumio Kamiyama, Ying-Shu Quan, Hidemasa Katsumi, Akira Yamamoto, Nan Qin, Shu Liu, Toshiyasu Sakane, Wenyan Niu and Wei Qiao and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Agricultural and Food Chemistry and Journal of Controlled Release.

In The Last Decade

Mei‐Na Jin

32 papers receiving 703 citations

Author Peers

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

Author Last Decade Papers Cites
Mei‐Na Jin 280 266 135 86 74 33 710
Shiv Bahadur 280 1.0× 220 0.8× 47 0.3× 44 0.5× 78 1.1× 55 895
Chul-Soon Yong 301 1.1× 188 0.7× 84 0.6× 18 0.2× 150 2.0× 30 713
Ashok Godavarthi 85 0.3× 213 0.8× 84 0.6× 76 0.9× 56 0.8× 30 740
Antonia Sacchi 102 0.4× 158 0.6× 106 0.8× 33 0.4× 39 0.5× 42 668
Kanji Noda 175 0.6× 206 0.8× 131 1.0× 25 0.3× 108 1.5× 34 672
Chadarat Ampasavate 124 0.4× 352 1.3× 30 0.2× 39 0.5× 96 1.3× 43 897
Laila Mahran 149 0.5× 212 0.8× 37 0.3× 24 0.3× 52 0.7× 28 725
Çiğdem Yücel 83 0.3× 181 0.7× 49 0.4× 52 0.6× 71 1.0× 39 623
Paul A. Lehman 367 1.3× 206 0.8× 364 2.7× 12 0.1× 35 0.5× 40 800
Weize Li 282 1.0× 235 0.9× 91 0.7× 9 0.1× 88 1.2× 28 677

Countries citing papers authored by Mei‐Na Jin

Since Specialization
Citations

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

Fields of papers citing papers by Mei‐Na Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mei‐Na Jin

This figure shows the co-authorship network connecting the top 25 collaborators of Mei‐Na Jin. A scholar is included among the top collaborators of Mei‐Na 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 Mei‐Na Jin. Mei‐Na 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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2026