Ming Lo

44 papers receiving 921 citations

Peers

Ming Lo
Comparison fields: 5 of 58
  • Cardiology and Cardiovascular Medicine 747
  • Endocrine and Autonomic Systems 25
  • Genetics 100
  • Physiology 78
  • Nephrology 27
Replace M Böhm with:
M Böhm Germany
Junhui Tan Canada
Carlos Díez-Freire United States
Jeffrey P. Cardinale United States
David J. Dzielak United States
KAZUHIRO IITAKE Japan
Regina Scivoletto Brazil
M. L. Grichois France
Anthony F Cutilletta United States
Bärbel Möhring Germany
Ming Lo relative to M Böhm Germany M Böhm's profile →
Citations per field
00.5×2×3.3×
M Böhm · 1×
Citations per year

Countries citing papers authored by Ming Lo

Since Specialization
Citations

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

Fields of papers citing papers by Ming Lo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1991259
2 1995126
3 199387
4 199340
5 199035
6 200734
7 199433
8 200127
9 199525
10 199925
11 199719
12 200319
13 199018
14 199118
15 199914
16 200314
17
Lyon genetically hypertensive rats: an animal model of "low renin hypertension".
200314
18 199813
19 200213
20 199112

About Ming Lo

Ming Lo is a scholar working on Cardiology and Cardiovascular Medicine, Endocrinology, Diabetes and Metabolism, Genetics, Nutrition and Dietetics and Pulmonary and Respiratory Medicine, having authored 45 papers that have together received 954 indexed citations. Recurring topics across this work include Renin-Angiotensin System Studies (23 papers), Blood Pressure and Hypertension Studies (11 papers), Heart Rate Variability and Autonomic Control (8 papers), Spaceflight effects on biology (2 papers), Sodium Intake and Health (2 papers), Renal and Vascular Pathologies (2 papers), Thyroid Disorders and Treatments (2 papers) and Hemoglobinopathies and Related Disorders (2 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (747 citations), Endocrine and Autonomic Systems (25 citations), Genetics (100 citations), Physiology (78 citations) and Nephrology (27 citations). Ming Lo has collaborated with scholars based in France, United Kingdom and Senegal. Frequent co-authors include Jean Sassard, M. Vincent, Catherine Cerutti, Claude Julien, Pierre Lantelme, Christian Zacharie Paultre, Marie‐Paule Gustin, Nilesh J. Samani, Gregory Mark Lathrop and Christian Barrès. Their work appears in journals such as American Journal of Physiology-Regulatory, Integrative and Comparative Physiology, Journal of Hypertension, Journal of Cardiovascular Pharmacology, American Journal of Hypertension and Hypertension.

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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