Kosuke Ishikawa

431 citations
27 papers · 284 · h-index 11

Impact in

Papers in

    • Ubiquitin and proteasome pathways 3
    • Viral Infectious Diseases and Gene Expression in Insects 3
    • Genomics and Chromatin Dynamics 3
    • CRISPR and Genetic Engineering 3

Kosuke Ishikawa

26 papers receiving 279 citations

Peers

Kosuke Ishikawa
Comparison fields: 5 of 67
  • Cancer Research 44
  • Cell Biology 47
  • Molecular Biology 167
  • Oncology 46
  • Immunology 37
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Máirín Rafferty Ireland
Melissa H. Chang Australia
Miki Tanaka Japan
Yvette Bren‐Mattison United States
Bhushan Thakur United States
Lele Cong China
Lei Ji China
Benjamin Green United States
Biqing Zhu China
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Citations per field
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Citations per year

Countries citing papers authored by Kosuke Ishikawa

Since Specialization
Citations

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

Fields of papers citing papers by Kosuke Ishikawa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200547
2 201430
3 201023
4 200921
5 200320
6 201220
7 201917
8 201617
9 201915
10 201612
11 201311
12 200510
13 20187
14 20056
15 20055
16 20214
17 20234
18 20023
19 20233
20 20222

About Kosuke Ishikawa

Kosuke Ishikawa is a scholar working on Molecular Biology, Oncology, Genetics, Computer Vision and Pattern Recognition and Cell Biology, having authored 27 papers that have together received 284 indexed citations. Recurring topics across this work include Virus-based gene therapy research (4 papers), Ubiquitin and proteasome pathways (3 papers), Viral Infectious Diseases and Gene Expression in Insects (3 papers), Interactive and Immersive Displays (3 papers), NF-κB Signaling Pathways (3 papers), Genomics and Chromatin Dynamics (3 papers), CRISPR and Genetic Engineering (3 papers) and Robotics and Sensor-Based Localization (2 papers). The work is most often cited by research in Cancer Research (44 citations), Cell Biology (47 citations), Molecular Biology (167 citations), Oncology (46 citations) and Immunology (37 citations). Kosuke Ishikawa has collaborated with scholars based in Japan, China and United States. Frequent co-authors include Kentaro Semba, Jun‐ichiro Inoue, Sakura Azuma, Shuntaro Ikawa, Taishin Akiyama, Shinya Watanabe, Jiro Fujimoto, Naoki Goshima, Koichi Ito and Mizuki Yamamoto. Their work appears in journals such as Gene, Biochemical and Biophysical Research Communications, International Journal of Molecular Sciences, Genes to Cells and Journal of Biological Chemistry.

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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