Ming Lu

1.1k citations
36 papers · 851 · h-index 15

Impact in

  • Aging top 5%
    • Genetics, Aging, and Longevity in Model Organisms
    • Cancer, Lipids, and Metabolism

Papers in

Ming Lu

35 papers receiving 832 citations

Peers

Ming Lu
Comparison fields: 5 of 94
  • Aging 60
  • Cancer Research 191
  • Endocrinology, Diabetes and Metabolism 209
  • Biochemistry 55
  • Physiology 171
Replace Motoyuki Igata with:
Motoyuki Igata Japan
Sandra Slusher United States
Robert W. Schwenk Netherlands
András Frankó Germany
Adama Kamagaté United States
Rebecca Quinn United States
James P. Stice United States
Sully Fernandez United States
Marko Z. Vatamaniuk United States
Fareeba Sheedfar Netherlands
Ming Lu relative to Motoyuki Igata Japan Motoyuki Igata's profile →
Citations per field
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Motoyuki Igata · 1×
Citations per year

Countries citing papers authored by Ming Lu

Since Specialization
Citations

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

Fields of papers citing papers by Ming Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014114
2 2017106
3 200275
4 199369
5 201361
6 199257
7 201446
8 201939
9 201335
10 201823
11 200822
12 201721
13 198820
14 199320
15 201417
16 199114
17 202114
18 202010
19 202210
20
[Pharmacokinetic analysis of enterohepatic circulation of piroxicam in rabbits].
19929

About Ming Lu

Ming Lu is a scholar working on Molecular Biology, Endocrinology, Diabetes and Metabolism, Surgery, Physiology and Cancer Research, having authored 36 papers that have together received 851 indexed citations. Recurring topics across this work include Peroxisome Proliferator-Activated Receptors (5 papers), Genetics, Aging, and Longevity in Model Organisms (4 papers), Pancreatic function and diabetes (4 papers), Thyroid Disorders and Treatments (4 papers), Metabolism, Diabetes, and Cancer (4 papers), Birth, Development, and Health (4 papers), Adipose Tissue and Metabolism (4 papers) and Cholesterol and Lipid Metabolism (4 papers). The work is most often cited by research in Aging (60 citations), Cancer Research (191 citations), Endocrinology, Diabetes and Metabolism (209 citations), Biochemistry (55 citations) and Physiology (171 citations). Ming Lu has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Ronald W. Hart, Ling Gao, Jiajun Zhao, Beverly Lyn‐Cook, Bruce S. Hass, Catherine C.Y. Chang, Ta‐Yuan Chang, Bo-Liang Li, Bao‐Liang Song and Chongbo Yang. Their work appears in journals such as Mechanisms of Ageing and Development, Acta Biochimica et Biophysica Sinica, Diabetes, Endocrine Connections and The Journal of Experimental Medicine.

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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