T. Magot

55 papers receiving 1.1k citations

Peers

T. Magot
Comparison fields: 5 of 75
  • Endocrinology, Diabetes and Metabolism 424
  • Cancer Research 214
  • Surgery 590
  • Cardiology and Cardiovascular Medicine 181
  • Biochemistry 41
Replace Elisabet Vilella with:
Elisabet Vilella Spain
Claude L. Malmendier Belgium
Jitske de Vries-van der Weij Netherlands
Jianyang Luo United States
S. Balasubramaniam Australia
Dagny Ståhlberg Sweden
K Nilsell Sweden
Yassine Zaïr France
S. Martini Italy
François Briand France
T. Magot relative to Elisabet Vilella Spain Elisabet Vilella's profile →
Citations per field
00.5×1.5×2.3×
Elisabet Vilella · 1×
Citations per year

Countries citing papers authored by T. Magot

Since Specialization
Citations

This map shows the geographic impact of T. Magot'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 T. Magot with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. Magot more than expected).

Fields of papers citing papers by T. Magot

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 55 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004151
2 198980
3 200770
4 199768
5 200359
6 199358
7 199947
8 198940
9 200238
10 200137
11 200337
12 199729
13 201127
14 200324
15 200623
16 201020
17 199018
18
A minimal model using stable isotopes to study the metabolism of apolipoprotein B-containing lipoproteins in humans.
199615
19 200614
20 200813

About T. Magot

T. Magot is a scholar working on Surgery, Endocrinology, Diabetes and Metabolism, Molecular Biology, Physiology and Epidemiology, having authored 55 papers that have together received 1.1k indexed citations. Recurring topics across this work include Diabetes, Cardiovascular Risks, and Lipoproteins (19 papers), Lipoproteins and Cardiovascular Health (19 papers), Cholesterol and Lipid Metabolism (18 papers), Lipid metabolism and disorders (10 papers), Peroxisome Proliferator-Activated Receptors (10 papers), Diet and metabolism studies (10 papers), Cancer, Lipids, and Metabolism (8 papers) and Adipose Tissue and Metabolism (7 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (424 citations), Cancer Research (214 citations), Surgery (590 citations), Cardiology and Cardiovascular Medicine (181 citations) and Biochemistry (41 citations). T. Magot has collaborated with scholars based in France, Belgium and Switzerland. Frequent co-authors include Khadija Ouguerram, Michel Krempf, Patrick Nguyen, Cyrille Maugeais, Yassine Zaïr, Claude L. Malmendier, F Chevallier, R. Frénais, C. Lutton and Maud Chétiveaux. Their work appears in journals such as Metabolism, Atherosclerosis, Advances in experimental medicine and biology, Arteriosclerosis Thrombosis and Vascular Biology and European Journal of Clinical Investigation.

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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