Eiichi Maeda

1.5k citations
30 papers · 290 · h-index 10

Impact in

Papers in

    • Peroxisome Proliferator-Activated Receptors 5
    • Cholesterol and Lipid Metabolism 5
    • Lipoproteins and Cardiovascular Health 4

Eiichi Maeda

29 papers receiving 279 citations

Peers

Eiichi Maeda
Comparison fields: 5 of 69
  • Endocrinology, Diabetes and Metabolism 80
  • Physiology 82
  • Clinical Biochemistry 20
  • Biochemistry 21
  • Cardiology and Cardiovascular Medicine 51
Replace Sibel Özyazgan with:
Sibel Özyazgan Türkiye
Geannyne Villegas-Rivera Mexico
Daniela Tomie Furuya Brazil
Masayoshi Ishizawa Japan
Asako Minami Japan
Wan Sub Shim South Korea
Francisco Moraga Chile
Gabriel G. Dorighello Brazil
Chuanshi Xiao China
Gang Yuan China
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Citations per field
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Citations per year

Countries citing papers authored by Eiichi Maeda

Since Specialization
Citations

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

Fields of papers citing papers by Eiichi Maeda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200736
2 199132
3 200129
4 199522
5 199318
6 199218
7 200715
8 200512
9 199311
10 19929
11 19929
12 19969
13
Effect of microsomal triglyceride transfer protein gene polymorphism in the promoter region on dyslipidemia in type 2 diabetic subjects.
20038
14 19987
15 19917
16 19977
17 20136
18
Noninvasive temperature measurement during moxibustion using MRI
20115
19
[Diabetes mellitus as a risk factor for arteriosclerosis].
19934
20 19894

About Eiichi Maeda

Eiichi Maeda is a scholar working on Molecular Biology, Surgery, Physiology, Endocrinology, Diabetes and Metabolism and Epidemiology, having authored 30 papers that have together received 290 indexed citations. Recurring topics across this work include Diet, Metabolism, and Disease (6 papers), Adipose Tissue and Metabolism (5 papers), Cholesterol and Lipid Metabolism (5 papers), Peroxisome Proliferator-Activated Receptors (5 papers), Cancer, Lipids, and Metabolism (4 papers), Lipid metabolism and biosynthesis (4 papers), Lipoproteins and Cardiovascular Health (4 papers) and Diabetes, Cardiovascular Risks, and Lipoproteins (3 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (80 citations), Physiology (82 citations), Clinical Biochemistry (20 citations), Biochemistry (21 citations) and Cardiology and Cardiovascular Medicine (51 citations). Eiichi Maeda has collaborated with scholars based in Japan, China and Spain. Frequent co-authors include Gen Yoshino, Masato Kasuga, Koh‐ichi Nagata, Yukio Murata, Tsutomu Kazumi, Hiroyuki Mori, Hideki Okazawa, Takashi Matozaki, Yasuo Akanuma and Tsutomu Hirano. Their work appears in journals such as Atherosclerosis, Journal of Lipid Research, Metabolism, Biochemical and Biophysical Research Communications and Coronary Artery Disease.

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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