Jin‐ichi Ito

1.2k citations
54 papers · 1.0k · h-index 19

Impact in

Papers in

    • Glycosylation and Glycoproteins Research 9
    • Fibroblast Growth Factor Research 7
    • Peroxisome Proliferator-Activated Receptors 4
    • Sphingolipid Metabolism and Signaling 4
    • Cholesterol and Lipid Metabolism 13

Jin‐ichi Ito

54 papers receiving 1.0k citations

Peers

Jin‐ichi Ito
Comparison fields: 5 of 86
  • Cell Biology 223
  • Developmental Neuroscience 49
  • Molecular Biology 633
  • Biochemistry 56
  • Neurology 59
Replace Hidenori Hattori with:
Hidenori Hattori Japan
Esther Barth Germany
Monika Poppe Germany
Xinle Wu United States
Bo‐Hwa Choi South Korea
Mu‐En Lin United States
Peter Pediaditakis United States
Tatiana Estrada-Hernandez United States
Manon Moulis France
Motoshi Sawada Japan
Jin‐ichi Ito relative to Hidenori Hattori Japan Hidenori Hattori's profile →
Citations per field
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Hidenori Hattori · 1×
Citations per year

Countries citing papers authored by Jin‐ichi Ito

Since Specialization
Citations

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

Fields of papers citing papers by Jin‐ichi Ito

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jin‐ichi Ito. 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 Jin‐ichi Ito. The network helps show where Jin‐ichi Ito may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 54 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200191
2 200086
3 200263
4 199963
5 200062
6 201634
7 198431
8 198130
9 201429
10 200229
11 200529
12 200426
13 201425
14 198824
15 200423
16 198622
17 200222
18 199920
19 198120
20 200618

About Jin‐ichi Ito

Jin‐ichi Ito is a scholar working on Molecular Biology, Surgery, Cell Biology, Cellular and Molecular Neuroscience and Physiology, having authored 54 papers that have together received 1.0k indexed citations. Recurring topics across this work include Cholesterol and Lipid Metabolism (13 papers), Caveolin-1 and cellular processes (10 papers), Glycosylation and Glycoproteins Research (9 papers), Fibroblast Growth Factor Research (7 papers), Neuroscience and Neuropharmacology Research (6 papers), Neurogenesis and neuroplasticity mechanisms (4 papers), Peroxisome Proliferator-Activated Receptors (4 papers) and Sphingolipid Metabolism and Signaling (4 papers). The work is most often cited by research in Cell Biology (223 citations), Developmental Neuroscience (49 citations), Molecular Biology (633 citations), Biochemistry (56 citations) and Neurology (59 citations). Jin‐ichi Ito has collaborated with scholars based in Japan, Iran and United States. Frequent co-authors include Shinji Yokoyama, Yuko Nagayasu, Taiji Kato, Ryo Tanaka, Makoto Michikawa, Sumiko Abe-Dohmae, Reijiro Arakawa, Alireza Kheirollah, Koichi Kato and Tatsuo Suzuki. Their work appears in journals such as Brain Research, Journal of Lipid Research, Journal of Neurochemistry, Developmental Brain Research and Proceedings of the Japan Academy Series B.

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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