Gen Tamiya

12.2k citations
132 papers · 3.4k · h-index 31

Impact in

  • Immunology top 5%
    • T-cell and B-cell Immunology
    • Immune Cell Function and Interaction
  • Genetics top 2%
    • Genetic Associations and Epidemiology
    • Genetic Mapping and Diversity in Plants and Animals

Papers in

    • Gene expression and cancer classification 5
    • Genetic Associations and Epidemiology 19
    • Genetic Mapping and Diversity in Plants and Animals 9
    • Genetic and phenotypic traits in livestock 6
    • Genetic diversity and population structure 5

Gen Tamiya

126 papers receiving 3.4k citations

Peers

Gen Tamiya
Comparison fields: 5 of 143
  • Immunology 612
  • Genetics 688
  • Neurology 258
  • Molecular Biology 1.1k
  • Health Informatics 20
Replace Simon Koplev with:
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Gen Tamiya relative to Simon Koplev United States Simon Koplev's profile →
Citations per field
00.5×4.7×
Simon Koplev · 1×
Citations per year

Countries citing papers authored by Gen Tamiya

Since Specialization
Citations

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

Fields of papers citing papers by Gen Tamiya

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 132 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007174
2 2019152
3 2005129
4 1999128
5 2004109
6 2004105
7 2020101
8 2014101
9 200899
10 200397
11 201994
12 200589
13 199988
14 200375
15 199869
16 201468
17 199867
18 201464
19
An efficient expression vector for transgenic medaka construction.
199464
20 200555

About Gen Tamiya

Gen Tamiya is a scholar working on Molecular Biology, Genetics, Immunology, Epidemiology and Genetics, having authored 132 papers that have together received 3.4k indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (19 papers), T-cell and B-cell Immunology (11 papers), Genetic Mapping and Diversity in Plants and Animals (9 papers), Immune Cell Function and Interaction (7 papers), Genetic and phenotypic traits in livestock (6 papers), Immunotherapy and Immune Responses (5 papers), Genetic diversity and population structure (5 papers) and Gene expression and cancer classification (5 papers). The work is most often cited by research in Immunology (612 citations), Genetics (688 citations), Neurology (258 citations), Molecular Biology (1.1k citations) and Health Informatics (20 citations). Gen Tamiya has collaborated with scholars based in Japan, Australia and United States. Frequent co-authors include Hidetoshi Inoko, Satoshi Makino, Akira Oka, Masao Ueki, Koichi Okamoto, Minoru Kimura, Takashi Shiina, M. Tomizawa, Satoshi Ando and Masao Ôta. Their work appears in journals such as The American Journal of Human Genetics, Gene, Scientific Reports, Genomics and Immunogenetics.

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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