Kayo Sumida

1.3k citations
50 papers · 950 · h-index 21

Impact in

    • Carcinogens and Genotoxicity Assessment
    • MicroRNA in disease regulation
    • Pharmacogenetics and Drug Metabolism

Papers in

    • Gene expression and cancer classification 9
    • Molecular Biology Techniques and Applications 8
    • Metabolomics and Mass Spectrometry Studies 4
    • Carcinogens and Genotoxicity Assessment 5

Kayo Sumida

50 papers receiving 927 citations

Peers

Kayo Sumida
Comparison fields: 5 of 106
  • Cancer Research 267
  • Pharmacology 143
  • Health, Toxicology and Mutagenesis 150
  • Developmental Neuroscience 33
  • Chemical Health and Safety 5
Replace Jorge M. Naciff with:
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Kayo Sumida relative to Jorge M. Naciff United States Jorge M. Naciff's profile →
Citations per field
00.5×2.8×
Jorge M. Naciff · 1×
Citations per year

Countries citing papers authored by Kayo Sumida

Since Specialization
Citations

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

Fields of papers citing papers by Kayo Sumida

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201465
2 200964
3 201157
4 201053
5 200645
6 201243
7 201436
8 200134
9 201129
10 201228
11 201328
12 201426
13 200825
14 202125
15 201723
16 201923
17 200322
18 200922
19 200121
20 200420

About Kayo Sumida

Kayo Sumida is a scholar working on Molecular Biology, Cancer Research, Genetics, Health, Toxicology and Mutagenesis and Oncology, having authored 50 papers that have together received 950 indexed citations. Recurring topics across this work include Gene expression and cancer classification (9 papers), Molecular Biology Techniques and Applications (8 papers), Estrogen and related hormone effects (6 papers), Pharmacogenetics and Drug Metabolism (5 papers), Computational Drug Discovery Methods (5 papers), Carcinogens and Genotoxicity Assessment (5 papers), Effects and risks of endocrine disrupting chemicals (5 papers) and Metabolomics and Mass Spectrometry Studies (4 papers). The work is most often cited by research in Cancer Research (267 citations), Pharmacology (143 citations), Health, Toxicology and Mutagenesis (150 citations), Developmental Neuroscience (33 citations) and Chemical Health and Safety (5 citations). Kayo Sumida has collaborated with scholars based in Japan, United States and United Kingdom. Frequent co-authors include Koichi Saito, Masahiko Kushida, Satoshi Kawamura, Hideo Kaneko, Hirohisa Nagahori, Satoshi Uwagawa, Tomoya Yamada, Tokuo Sukata, Kaori Miyata and Brian G. Lake. Their work appears in journals such as Toxicological Sciences, Biochemical and Biophysical Research Communications, Toxicology and Applied Pharmacology, Environmental Toxicology and Chemistry and Toxicology Letters.

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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