Ming-May Lai

633 citations
15 papers · 486 · h-index 10

Impact in

    • Microbial Metabolism and Applications
  • Pharmacology top 10%
    • Pharmacological Effects of Natural Compounds

Papers in

Ming-May Lai

15 papers receiving 467 citations

Peers

Ming-May Lai
Comparison fields: 5 of 86
  • Biotechnology 112
  • Pharmacology 79
  • Geriatrics and Gerontology 25
  • Biochemistry 33
  • Endocrinology, Diabetes and Metabolism 90
Replace Maria Virginia Manzi with:
Maria Virginia Manzi Italy
Grzegorz K. Jakubiak Poland
Mohammad Abbasinazari Iran
Ammar Salehi‐Sahlabadi Iran
Mateusz Lejawa Poland
Marijan Bosevski North Macedonia
Kamila Osadnik Poland
Margarita Petermann Chile
M. G. Sridhar India
Susan E. Aeschlimann United States
Ming-May Lai relative to Maria Virginia Manzi Italy Maria Virginia Manzi's profile →
Citations per field
00.5×5.3×
Maria Virginia Manzi · 1×
Citations per year

Countries citing papers authored by Ming-May Lai

Since Specialization
Citations

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

Fields of papers citing papers by Ming-May Lai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

15 of 15 papers shown
#Work
1 2005109
2 200767
3 200762
4 200752
5 201844
6 201034
7 200929
8 200924
9 202018
10 201517
11 20039
12 20119
13 20185
14 20144
15 20113

About Ming-May Lai

Ming-May Lai is a scholar working on Epidemiology, Endocrinology, Diabetes and Metabolism, Physiology, Surgery and Cardiology and Cardiovascular Medicine, having authored 15 papers that have together received 486 indexed citations. Recurring topics across this work include Adipokines, Inflammation, and Metabolic Diseases (5 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (4 papers), Body Composition Measurement Techniques (2 papers), Diabetes Management and Research (2 papers), Diabetes Management and Education (2 papers), Microbial Metabolism and Applications (2 papers), Adipose Tissue and Metabolism (2 papers) and Pharmacological Effects of Natural Compounds (2 papers). The work is most often cited by research in Biotechnology (112 citations), Pharmacology (79 citations), Geriatrics and Gerontology (25 citations), Biochemistry (33 citations) and Endocrinology, Diabetes and Metabolism (90 citations). Ming-May Lai has collaborated with scholars based in Taiwan, China and United States. Frequent co-authors include Cheng‐Chieh Lin, Tsai‐Chung Li, Chiu-Shong Liu, Wen‐Yuan Lin, Chia-Ing Li, Ching-Chu Chen, Ming‐Tsang Wu, Tsann Lin, Chih-Hsueh Lin and Shih-Wei Lai. Their work appears in journals such as BMC Public Health, International Journal of Stroke, European Journal of Endocrinology, BMJ Open and Aging.

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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