Mei Ling Jin

15 total papers · 729 total citations
13 papers, 601 citations indexed

About

Mei Ling Jin is a scholar working on Molecular Biology, Neurology and Pharmacology. According to data from OpenAlex, Mei Ling Jin has authored 13 papers receiving a total of 601 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 5 papers in Neurology and 3 papers in Pharmacology. Recurrent topics in Mei Ling Jin's work include Neuroinflammation and Neurodegeneration Mechanisms (5 papers), Genomics, phytochemicals, and oxidative stress (4 papers) and Pharmacological Effects of Natural Compounds (2 papers). Mei Ling Jin is often cited by papers focused on Neuroinflammation and Neurodegeneration Mechanisms (5 papers), Genomics, phytochemicals, and oxidative stress (4 papers) and Pharmacological Effects of Natural Compounds (2 papers). Mei Ling Jin collaborates with scholars based in South Korea, China and United States. Mei Ling Jin's co-authors include Sun Young Park, Geuntae Park, Young Whan Choi, Min Jung Ko, Young Hun Kim, Sang Joon Lee, Yanchun Zhao, Jin Wang, Yunhao Chen and Scott A. Coonrod and has published in prestigious journals such as Developmental Biology, Food and Chemical Toxicology and Theranostics.

In The Last Decade

Mei Ling Jin

13 papers receiving 597 citations

Author Peers

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

Author						Papers	Cites
Mei Ling Jin	304	82	71	68	63	13	601
Angélica Guerrero‐Castilla	244 0.8×	52 0.6×	69 1.0×	92 1.4×	33 0.5×	16	646
Entaz Bahar	268 0.9×	53 0.6×	55 0.8×	45 0.7×	43 0.7×	18	673
Prahalathan Pichavaram	274 0.9×	58 0.7×	34 0.5×	85 1.3×	40 0.6×	26	684
Yuxuan Kan	230 0.8×	74 0.9×	50 0.7×	49 0.7×	28 0.4×	25	563
Amin Iranpanah	265 0.9×	85 1.0×	41 0.6×	35 0.5×	37 0.6×	23	695
Juanli Fu	317 1.0×	76 0.9×	56 0.8×	104 1.5×	35 0.6×	19	668
Ya‐Ge Jin	306 1.0×	97 1.2×	65 0.9×	57 0.8×	23 0.4×	18	613
Sarvjeet Singh	333 1.1×	48 0.6×	44 0.6×	94 1.4×	23 0.4×	11	684
Hwa Jin Jang	309 1.0×	99 1.2×	58 0.8×	110 1.6×	65 1.0×	13	608
Liping Bao	286 0.9×	48 0.6×	39 0.5×	130 1.9×	28 0.4×	11	622

Countries citing papers authored by Mei Ling Jin

Since Specialization

Citations

This map shows the geographic impact of Mei Ling 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 Ling 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 Ling Jin more than expected).

Fields of papers citing papers by Mei Ling Jin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mei Ling Jin

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