Masahiro Koseki
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- Diet, Metabolism, and Disease 7
- Diabetes, Cardiovascular Risks, and Lipoproteins 5
- Hepatology top 5%
- Epidemiology top 5%
- Liver Disease Diagnosis and Treatment 10
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- Lipid metabolism and disorders 14
- Surgery top 10%
- Cholesterol and Lipid Metabolism 15
- Lipoproteins and Cardiovascular Health 9
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- Peroxisome Proliferator-Activated Receptors 15
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- Cancer, Lipids, and Metabolism 12
Masahiro Koseki
55 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 92
- Endocrinology, Diabetes and Metabolism 371
- Hepatology 127
- Epidemiology 529
- Cardiology and Cardiovascular Medicine 283
- Surgery 468
Countries citing papers authored by Masahiro Koseki
This map shows the geographic impact of Masahiro Koseki'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 Masahiro Koseki with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Masahiro Koseki more than expected).
Fields of papers citing papers by Masahiro Koseki
This network shows the impact of papers produced by Masahiro Koseki. 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 Masahiro Koseki. The network helps show where Masahiro Koseki may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Masahiro Koseki, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 0 | |
| 4 | 2023 | 15 | |
| 5 | 2021 | 39 | |
| 6 | 2020 | 1 | |
| 7 | 2020 | 13 | |
| 8 | 2020 | 50 | |
| 9 | 2020 | 26 | |
| 10 | 2020 | 1 | |
| 11 | EDMOND and SonotaCo net | 2019 | 0 |
| 12 | 2019 | 12 | |
| 13 | Abstract 16439: Proteomic Analysis of Atherogenic Chylomicron Remnants Isolated Selectively From Human Serum | 2016 | 1 |
| 14 | 2016 | 7 | |
| 15 | Abstract 14993: Proteomic Analysis of Chylomicron Remnants Isolated by Apolipoprotein B-48 Immunoprecipitation | 2014 | 1 |
| 16 | 2008 | 87 | |
| 17 | 2008 | 12 | |
| 18 | 2005 | 13 | |
| 19 | Vesicular Acidification Is Required for ATP-Binding Cassette Transporter A1-Mediated Cholesterol Efflux | 2003 | 1 |
| 20 | Measurement of Cholesterol Efflux from Monocyte-Derived Macrophages of Patients with Llpid Disorders and Atherosclerotic Cardiovascular Diseases | 2003 | 1 |
About Masahiro Koseki
Masahiro Koseki is a scholar working on Cardiology and Cardiovascular Medicine, Endocrinology, Diabetes and Metabolism and Cancer Research, having authored 62 papers that have together received 1.3k indexed citations. Recurring topics across this work include Cholesterol and Lipid Metabolism (15 papers), Peroxisome Proliferator-Activated Receptors (15 papers), Lipid metabolism and disorders (14 papers), Cancer, Lipids, and Metabolism (12 papers), Liver Disease Diagnosis and Treatment (10 papers), Lipoproteins and Cardiovascular Health (9 papers), Diet, Metabolism, and Disease (7 papers) and Diabetes, Cardiovascular Risks, and Lipoproteins (5 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (371 citations), Hepatology (127 citations) and Epidemiology (529 citations). Masahiro Koseki has collaborated with scholars based in Japan, United States and Netherlands. Frequent co-authors include Daisaku Masuda, Makoto Nishida, Shizuya Yamashita, Iichiro Shimomura, Fumihiko Matsuura, José C. Sandoval, Ken‐ichi Hirano, Tohru Ohama, Masato Ishigami and Hiroyuki Oku. Their work appears in journals such as Nature, Circulation and Journal of the American College of Cardiology.
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.