Ming Jin

609 citations
21 papers · 442 · h-index 9

Impact in

  • Nephrology top 5%
    • Gout, Hyperuricemia, Uric Acid
  • Toxicology top 10%
    • Forensic Toxicology and Drug Analysis

Papers in

Ming Jin

18 papers receiving 431 citations

Peers

Ming Jin
Comparison fields: 5 of 94
  • Nephrology 194
  • Toxicology 27
  • Pathology and Forensic Medicine 93
  • Biological Psychiatry 12
  • Hepatology 33
Replace A Lum Han with:
A Lum Han South Korea
Tadashi Imafuku Japan
Heidi Koivisto Finland
Weijie Liu China
Jesús Macarrón‐Vicente Spain
Jun-ichi Yamakita Japan
Seo H Japan
Hooi Hooi Ng Australia
Nadezda V. Andrianova Russia
Ming Jin relative to A Lum Han South Korea A Lum Han's profile →
Citations per field
00.5×6.9×
A Lum Han · 1×
Citations per year

Countries citing papers authored by Ming Jin

Since Specialization
Citations

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

Fields of papers citing papers by Ming Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ming 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 Ming Jin Line = papers co-authored together Ming Jin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011291
2 201128
3 202025
4 200821
5 201217
6 202212
7 20159
8 20119
9 20188
10 20137
11 20184
12 20183
13 20242
14 20242
15 20241
16 20241
17
[Separation and determination of aconitine in medicine wine by reversed-phase high performance liquid chromatography].
20051
18
Inducible Expression of bcl-2 Antisense RNA Promotes Apoptosis of Human Gastric Cancer Cell Line.
19991
19 20250
20 20250

About Ming Jin

Ming Jin is a scholar working on Pharmacology, Surgery, Pathology and Forensic Medicine, Pharmacology and Psychiatry and Mental health, having authored 21 papers that have together received 442 indexed citations. Recurring topics across this work include Neutrophil, Myeloperoxidase and Oxidative Mechanisms (2 papers), Psychedelics and Drug Studies (2 papers), Anesthesia and Pain Management (2 papers), Liver Disease Diagnosis and Treatment (2 papers), Cancer, Stress, Anesthesia, and Immune Response (2 papers), Forensic Toxicology and Drug Analysis (2 papers), Plant-based Medicinal Research (2 papers) and MicroRNA in disease regulation (1 paper). The work is most often cited by research in Nephrology (194 citations), Toxicology (27 citations), Pathology and Forensic Medicine (93 citations), Biological Psychiatry (12 citations) and Hepatology (33 citations). Ming Jin has collaborated with scholars based in China, United States and South Korea. Frequent co-authors include Hye Hyun Yoo, Moon Kyo In, Keane K. Y. Lai, Jason A. Dominitz, Shan Yuan, Daniel D. Bankson, Jaeick Lee, Jiangeng Huang, Toshinari Minamoto and Hua Wang. Their work appears in journals such as Journal of Forensic Sciences, Biological Psychiatry, British Journal of Cancer, Medicine and Frontiers in bioscience.

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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