Ming Jin

29 total papers · 602 total citations
20 papers, 440 citations indexed

About

Ming Jin is a scholar working on Pharmacology, Surgery and Pathology and Forensic Medicine. According to data from OpenAlex, Ming Jin has authored 20 papers receiving a total of 440 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Pharmacology, 3 papers in Surgery and 3 papers in Pathology and Forensic Medicine. Recurrent topics in Ming Jin's work include Cancer, Stress, Anesthesia, and Immune Response (2 papers), Anesthesia and Pain Management (2 papers) and Liver Disease Diagnosis and Treatment (2 papers). Ming Jin is often cited by papers focused on Cancer, Stress, Anesthesia, and Immune Response (2 papers), Anesthesia and Pain Management (2 papers) and Liver Disease Diagnosis and Treatment (2 papers). Ming Jin collaborates with scholars based in China, United States and South Korea. Ming Jin's co-authors include Hye Hyun Yoo, Moon Kyo In, Jason A. Dominitz, Daniel D. Bankson, Keane K. Y. Lai, Shan Yuan, Jaeick Lee, Jiangeng Huang, Hua Wang and Jianguo Chen and has published in prestigious journals such as Biological Psychiatry, British Journal of Cancer and Clinical Chemistry.

In The Last Decade

Ming Jin

18 papers receiving 429 citations

Author Peers

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

Author						Papers	Cites
Ming Jin	194	128	93	66	62	20	440
Yanhuan Feng	156 0.8×	167 1.3×	50 0.5×	41 0.6×	75 1.2×	27	453
Arnold Kooij	193 1.0×	243 1.9×	80 0.9×	32 0.5×	33 0.5×	17	464
S. Margolin	53 0.3×	92 0.7×	30 0.3×	37 0.6×	53 0.9×	28	455
Ruhan Jia	116 0.6×	146 1.1×	32 0.3×	35 0.5×	37 0.6×	31	425
Emanuela Cecchin	90 0.5×	53 0.4×	82 0.9×	33 0.5×	47 0.8×	19	448
Dina O. Abdulazim	292 1.5×	127 1.0×	107 1.2×	76 1.2×	69 1.1×	27	470
Chun‐Wu Tung	228 1.2×	165 1.3×	63 0.7×	70 1.1×	82 1.3×	22	455
Mona M. Salem	313 1.6×	132 1.0×	109 1.2×	77 1.2×	66 1.1×	23	494
William C. Kuzell	109 0.6×	97 0.8×	23 0.2×	33 0.5×	61 1.0×	24	476
Maha H. Sharawy	31 0.2×	134 1.0×	44 0.5×	71 1.1×	60 1.0×	27	451

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-authorship network of co-authors of Ming Jin

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