Satoshi Ugi

4.5k citations
111 papers · 3.6k · h-index 35

Impact in

Papers in

    • Metabolism, Diabetes, and Cancer 17
    • Protein Kinase Regulation and GTPase Signaling 17
    • Protein Tyrosine Phosphatases 12
    • Bariatric Surgery and Outcomes 9
    • Pancreatic function and diabetes 8

Satoshi Ugi

110 papers receiving 3.5k citations

Peers

Satoshi Ugi
Comparison fields: 5 of 112
  • Nephrology 214
  • Physiology 762
  • Endocrinology, Diabetes and Metabolism 433
  • Molecular Biology 1.7k
  • Biochemistry 171
Replace M. Julia Brosnan with:
M. Julia Brosnan United Kingdom
Stefano Menini Italy
Gema Medina‐Gómez Spain
Hongting Zheng China
Raffaella Mastrocola Italy
Shokei Kim‐Mitsuyama Japan
Yoshihiko Nishio Japan
Jan Galle Germany
Xue Du China
I. George Fantus Canada
Satoshi Ugi relative to M. Julia Brosnan United Kingdom M. Julia Brosnan's profile →
Citations per field
00.5×1.6×
M. Julia Brosnan · 1×
Citations per year

Countries citing papers authored by Satoshi Ugi

Since Specialization
Citations

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

Fields of papers citing papers by Satoshi Ugi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 111 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015273
2 2004198
3 2019162
4 1999138
5 2001112
6 2012112
7 201188
8 200182
9 201280
10 200279
11 201878
12 199975
13 199575
14 200370
15 201370
16 201068
17 200267
18 201564
19 201460
20 199956

About Satoshi Ugi

Satoshi Ugi is a scholar working on Molecular Biology, Surgery, Physiology, Epidemiology and Endocrinology, Diabetes and Metabolism, having authored 111 papers that have together received 3.6k indexed citations. Recurring topics across this work include Metabolism, Diabetes, and Cancer (17 papers), Protein Kinase Regulation and GTPase Signaling (17 papers), Adipose Tissue and Metabolism (12 papers), Protein Tyrosine Phosphatases (12 papers), Adipokines, Inflammation, and Metabolic Diseases (12 papers), Bariatric Surgery and Outcomes (9 papers), Diabetes Treatment and Management (9 papers) and Pancreatic function and diabetes (8 papers). The work is most often cited by research in Nephrology (214 citations), Physiology (762 citations), Endocrinology, Diabetes and Metabolism (433 citations), Molecular Biology (1.7k citations) and Biochemistry (171 citations). Satoshi Ugi has collaborated with scholars based in Japan, United States and South Korea. Frequent co-authors include Hiroshi Maegawa, Atsunori Kashiwagi, Katsutaro Morino, Jerrold M. Olefsky, Takeshi Imamura, Yoshihiko Nishio, Takeshi Yoshizaki, Osamu Sekine, Katsuya Egawa and Shinji Kume. Their work appears in journals such as Biochemical and Biophysical Research Communications, Journal of Biological Chemistry, PLoS ONE, Diabetes Research and Clinical Practice and Diabetes.

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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