Satoshi UNE

724 citations
56 papers · 555 · h-index 15

Impact in

Papers in

    • Pancreatic function and diabetes 15
    • Xenotransplantation and immune response 5
    • Tissue Engineering and Regenerative Medicine 3
    • Virus-based gene therapy research 6

Satoshi UNE

54 papers receiving 528 citations

Peers

Satoshi UNE
Comparison fields: 5 of 74
  • Reproductive Medicine 70
  • Parasitology 46
  • Small Animals 45
  • Dermatology 47
  • Genetics 137
Replace Tetsuya NAKADE with:
Tetsuya NAKADE Japan
Silvia Ferro Italy
T. Hayashi Japan
C Tarantino Italy
Juana Martín de las Mulas Spain
Hannamari Välimaa Finland
G. L. Watson United States
Leigh Ann Jones United Kingdom
Peter S. MacWilliams United States
Satoshi UNE relative to Tetsuya NAKADE Japan Tetsuya NAKADE's profile →
Citations per field
00.5×
Tetsuya NAKADE · 1×
Citations per year

Countries citing papers authored by Satoshi UNE

Since Specialization
Citations

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

Fields of papers citing papers by Satoshi UNE

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 56 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200056
2 200030
3 200228
4 200228
5 200027
6 200427
7 199822
8 200121
9 199520
10 200519
11 200419
12 200117
13 199216
14 200515
15 200615
16 200214
17 199813
18 199513
19 200713
20 200712

About Satoshi UNE

Satoshi UNE is a scholar working on Surgery, Genetics, Molecular Biology, Epidemiology and Oncology, having authored 56 papers that have together received 555 indexed citations. Recurring topics across this work include Pancreatic function and diabetes (15 papers), Virus-based gene therapy research (6 papers), Diabetes Management and Research (5 papers), Xenotransplantation and immune response (5 papers), Cannabis and Cannabinoid Research (4 papers), Herpesvirus Infections and Treatments (4 papers), Hedgehog Signaling Pathway Studies (4 papers) and Tissue Engineering and Regenerative Medicine (3 papers). The work is most often cited by research in Reproductive Medicine (70 citations), Parasitology (46 citations), Small Animals (45 citations), Dermatology (47 citations) and Genetics (137 citations). Satoshi UNE has collaborated with scholars based in Japan and United States. Frequent co-authors include Munekazu NAKAICHI, Yasuho TAURA, Yoko Mullen, Takeshige Otoi, Masaru Okuda, Kazuhito ITAMOTO, Seiji Arita, Masahiro Morimoto, Kenji Tani and Sanenori NAKAMA. Their work appears in journals such as Pancreas, Veterinary Record, Research in Veterinary Science, Transplantation and Journal of Veterinary Medical Science.

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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