Meng Jin

1.8k citations
89 papers · 1.4k · h-index 22

Impact in

  • Neurology top 5%
    • Neuroinflammation and Neurodegeneration Mechanisms
    • Zebrafish Biomedical Research Applications

Papers in

Meng Jin

83 papers receiving 1.4k citations

Peers

Meng Jin
Comparison fields: 5 of 136
  • Neurology 144
  • Cell Biology 247
  • Health, Toxicology and Mutagenesis 196
  • Complementary and alternative medicine 99
  • Pharmacology 188
Replace Liwen Han with:
Liwen Han China
Hyun Chul Koh South Korea
Palaniyandi Ravanan India
Chunqi Li China
Shailendra K. Gupta India
Qian Bu China
Cheng‐Fang Tsai Taiwan
Man‐Jeong Paik South Korea
Gholam Hossein Riazi Iran
Alessandra Mocali Italy
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Citations per field
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Citations per year

Countries citing papers authored by Meng Jin

Since Specialization
Citations

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

Fields of papers citing papers by Meng Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Meng Jin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Meng Jin Line = papers co-authored together Meng Jin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 89 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020111
2 201968
3 201957
4 201951
5 201945
6 201844
7 202044
8 201942
9 202141
10 201936
11 201835
12 201933
13 202133
14 202132
15 202131
16 202230
17 202130
18 201129
19 202029
20 201927

About Meng Jin

Meng Jin is a scholar working on Molecular Biology, Cell Biology, Neurology, Epidemiology and Pharmacology, having authored 89 papers that have together received 1.4k indexed citations. Recurring topics across this work include Zebrafish Biomedical Research Applications (17 papers), Neuroinflammation and Neurodegeneration Mechanisms (16 papers), Autophagy in Disease and Therapy (10 papers), Neuroscience and Neuropharmacology Research (6 papers), Berberine and alkaloids research (6 papers), Environmental Toxicology and Ecotoxicology (6 papers), Parkinson's Disease Mechanisms and Treatments (5 papers) and Developmental Biology and Gene Regulation (5 papers). The work is most often cited by research in Neurology (144 citations), Cell Biology (247 citations), Health, Toxicology and Mutagenesis (196 citations), Complementary and alternative medicine (99 citations) and Pharmacology (188 citations). Meng Jin has collaborated with scholars based in China, Hungary and United Kingdom. Frequent co-authors include Kechun Liu, Xiuna Ji, Shanshan Zhang, Wenlong Sheng, Lizhen Wang, Attila Sı́k, Xiang Li, Rongchun Wang, Baoyue Zhang and Yam Nath Paudel. Their work appears in journals such as The Science of The Total Environment, Chemosphere, Comparative Biochemistry and Physiology Part C Toxicology & Pharmacology, PLoS ONE and Bioorganic Chemistry.

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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