Ming‐Yi Shen

2.4k citations
80 papers · 2.1k · h-index 26

Impact in

Papers in

Ming‐Yi Shen

77 papers receiving 2.0k citations

Peers

Ming‐Yi Shen
Comparison fields: 5 of 124
  • Biochemistry 217
  • Geriatrics and Gerontology 78
  • Clinical Biochemistry 94
  • Pharmacology 223
  • Hematology 142
Replace Hiromichi Wada with:
Hiromichi Wada Japan
Being‐Sun Wung Taiwan
Montserrat Rojo de la Vega United States
Po‐Len Liu Taiwan
Mi Jeong Sung South Korea
Wei Deng China
Junichiro Yamamoto Japan
Heqing Huang China
Ebtehal El‐Demerdash Egypt
Heqing Huang China
Ming‐Yi Shen relative to Hiromichi Wada Japan Hiromichi Wada's profile →
Citations per field
00.5×2×3.0×
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 2003213
2 2004131
3 2007131
4 200477
5 201572
6 201369
7 200364
8 200258
9 201556
10 200553
11 200550
12 201048
13 200844
14 200541
15 201533
16 200432
17 201732
18 200631
19 202131
20 201931

About Ming‐Yi Shen

Ming‐Yi Shen is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine, Surgery, Hematology and Biochemistry, having authored 80 papers that have together received 2.1k indexed citations. Recurring topics across this work include Antiplatelet Therapy and Cardiovascular Diseases (13 papers), Antioxidant Activity and Oxidative Stress (7 papers), Platelet Disorders and Treatments (6 papers), Blood Coagulation and Thrombosis Mechanisms (5 papers), Cholesterol and Lipid Metabolism (5 papers), Protein Interaction Studies and Fluorescence Analysis (4 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (4 papers) and Coagulation, Bradykinin, Polyphosphates, and Angioedema (4 papers). The work is most often cited by research in Biochemistry (217 citations), Geriatrics and Gerontology (78 citations), Clinical Biochemistry (94 citations), Pharmacology (223 citations) and Hematology (142 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, Tzeng‐Fu Chen, Duen S. Chou and Ching-Hua Su. 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 Biochemical 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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