Jun Hosoe

608 citations
7 papers · 98 · h-index 4

Impact in

Papers in

    • Protein Kinase Regulation and GTPase Signaling 2
    • Genomics and Chromatin Dynamics 1
    • RNA Research and Splicing 1
    • Genetic Associations and Epidemiology 2
    • Genomics and Rare Diseases 1
    • Genetic Mapping and Diversity in Plants and Animals 1

Jun Hosoe

7 papers receiving 98 citations

Peers

Jun Hosoe
Comparison fields: 5 of 28
  • Endocrinology, Diabetes and Metabolism 22
  • Genetics 28
  • Surgery 29
  • Physiology 17
  • Molecular Biology 41
Replace Khushdeep Bandesh with:
Khushdeep Bandesh India
Jordi Rodó Spain
Nicole Sheanon United States
Raphaël Boutry France
Divya Sri Priyanka Tallapragada India
Ulrich Stifel Germany
Nataša Rojnić Putarek Croatia
Shiying Guo China
Victor Sacristan Spain
P Chapman United Kingdom
Jun Hosoe relative to Khushdeep Bandesh India Khushdeep Bandesh's profile →
Citations per field
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Khushdeep Bandesh · 1×
Citations per year

Countries citing papers authored by Jun Hosoe

Since Specialization
Citations

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

Fields of papers citing papers by Jun Hosoe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

7 of 7 papers shown
#Work
1 201447
2 201731
3 20149
4 20216
5 20212
6 20182
7 20191

About Jun Hosoe

Jun Hosoe is a scholar working on Molecular Biology, Genetics, Endocrinology, Diabetes and Metabolism, Surgery and Infectious Diseases, having authored 7 papers that have together received 98 indexed citations. Recurring topics across this work include Protein Kinase Regulation and GTPase Signaling (2 papers), Genetic Associations and Epidemiology (2 papers), Genomics and Chromatin Dynamics (1 paper), RNA Research and Splicing (1 paper), Genomics and Rare Diseases (1 paper), Genetic Mapping and Diversity in Plants and Animals (1 paper), Diabetes Treatment and Management (1 paper) and Diabetes Management and Research (1 paper). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (22 citations), Genetics (28 citations), Surgery (29 citations), Physiology (17 citations) and Molecular Biology (41 citations). Jun Hosoe has collaborated with scholars based in Japan and Australia. Frequent co-authors include Nobuhiro Shojima, Takashi Kadowaki, Kazuo Hara, Toshimasa Yamauchi, Shoji Tsuji, Hiroyuki Ishiura, Ken Suzuki, Takeru Ito, Keith A. Boroevich and Tomoyuki Kawamura. Their work appears in journals such as Diabetes, Obesity, Cochrane Database of Systematic Reviews, Biochemical and Biophysical Research Communications and Human Genome Variation.

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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