Ming‐Yi Shen

77 papers receiving 1.9k citations

Peers

Ming‐Yi Shen
Comparison fields: 5 of 125
  • Biochemistry 232
  • Geriatrics and Gerontology 79
  • Clinical Biochemistry 104
  • Pharmacology 129
  • Hematology 163
Replace Hiromichi Wada with:
Hiromichi Wada Japan
Lu Lu China
Montserrat Rojo de la Vega United States
Mi Jeong Sung South Korea
Fabio M. Pulcinelli Italy
Anthony Zulli Australia
Liansheng Wang China
Wei Deng China
Maria-Corina Șerban Romania
Junichiro Yamamoto Japan
Ming‐Yi Shen relative to Hiromichi Wada Japan Hiromichi Wada's profile →
Citations per field
00.5×3.1×
Hiromichi Wada · 1×
Citations per year

Countries citing papers authored by Ming‐Yi Shen

Since Specialization
Citations

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

Fields of papers citing papers by Ming‐Yi Shen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 80 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003209
2 2004124
3 2007123
4 200473
5 201570
6 201368
7 200257
8 200357
9 201555
10 200549
11 201047
12 200545
13 200842
14 200537
15 200432
16 201732
17 201931
18 201531
19 200630
20 200930

About Ming‐Yi Shen

Ming‐Yi Shen is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine, Surgery, Immunology and Hematology, having authored 80 papers that have together received 2.0k indexed citations. Recurring topics across this work include Antiplatelet Therapy and Cardiovascular Diseases (13 papers), Antioxidant Activity and Oxidative Stress (8 papers), Atherosclerosis and Cardiovascular Diseases (7 papers), Lipoproteins and Cardiovascular Health (7 papers), Blood Coagulation and Thrombosis Mechanisms (6 papers), Cholesterol and Lipid Metabolism (6 papers), Platelet Disorders and Treatments (6 papers) and Diabetes, Cardiovascular Risks, and Lipoproteins (5 papers). The work is most often cited by research in Biochemistry (232 citations), Geriatrics and Gerontology (79 citations), Clinical Biochemistry (104 citations), Pharmacology (129 citations) and Hematology (163 citations). Ming‐Yi Shen has collaborated with scholars based in Taiwan, United States and China. Frequent co-authors include Joen‐Rong Sheu, George Hsiao, Duen‐Suey Chou, Chien‐Huang Lin, Kuan‐Hung Lin, Joen R. Sheu, George Hsiao, An‐Sheng Lee, Ching-Hua Su and Tzeng‐Fu Chen. Their work appears in journals such as Journal of Biomedical Science, Journal of Agricultural and Food Chemistry, International Journal of Molecular Sciences, PLoS ONE and European Journal of Pharmacology.

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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