R Takeda

680 citations
37 papers · 548 · h-index 13

Impact in

Papers in

    • Lipoproteins and Cardiovascular Health 9
    • Pancreatic function and diabetes 4
    • Hormonal Regulation and Hypertension 5
    • Diabetes, Cardiovascular Risks, and Lipoproteins 4
    • Hormonal and reproductive studies 4

R Takeda

31 papers receiving 521 citations

Peers

R Takeda
Comparison fields: 5 of 74
  • Endocrinology, Diabetes and Metabolism 192
  • Cancer Research 110
  • Surgery 301
  • Endocrinology 26
  • Cardiology and Cardiovascular Medicine 95
Replace Kiyosumi Takaishi with:
Kiyosumi Takaishi Japan
Daniel Ferguson United States
Eung Jae Yoo South Korea
Ángela Vinué Spain
Deborah L. Wilson United States
C T Chan United States
Tayze T. Antunes Canada
Hak‐Joong Kim United States
Nikola Radović Serbia
Hongying An United States
R Takeda relative to Kiyosumi Takaishi Japan Kiyosumi Takaishi's profile →
Citations per field
00.5×10×13×
Kiyosumi Takaishi · 1×
Citations per year

Countries citing papers authored by R Takeda

Since Specialization
Citations

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

Fields of papers citing papers by R Takeda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 198687
2 197785
3 199456
4 198838
5 197837
6 197534
7 197732
8 197923
9 202023
10 199419
11 199214
12 198814
13 199112
14 202211
15 198611
16 19849
17 19918
18 20247
19 20216
20 20014

About R Takeda

R Takeda is a scholar working on Surgery, Endocrinology, Diabetes and Metabolism, Physiology, Molecular Biology and Cancer Research, having authored 37 papers that have together received 548 indexed citations. Recurring topics across this work include Adipose Tissue and Metabolism (10 papers), Lipoproteins and Cardiovascular Health (9 papers), Cancer, Lipids, and Metabolism (5 papers), Hormonal Regulation and Hypertension (5 papers), Exercise and Physiological Responses (5 papers), Pancreatic function and diabetes (4 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (4 papers) and Hormonal and reproductive studies (4 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (192 citations), Cancer Research (110 citations), Surgery (301 citations), Endocrinology (26 citations) and Cardiology and Cardiovascular Medicine (95 citations). R Takeda has collaborated with scholars based in Japan, United States and Canada. Frequent co-authors include Hiroshi Mabuchi, Kosei Ueda, Tadayoshi Takegoshi, Susumu Miyamoto, Takanobu WAKASUGI, Jun‐ichi Koizumi, Masayuki Ohta, Toshihiro Haba, Isamu Miyamori and Ryosei Ueda. Their work appears in journals such as Atherosclerosis, Experimental and Clinical Endocrinology & Diabetes, The FASEB Journal, American Journal of Physiology-Regulatory, Integrative and Comparative Physiology and Scientific Reports.

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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