Kazuyo Takeda
- Immunology top 2%
- Immune Cell Function and Interaction 10
- T-cell and B-cell Immunology 10
- Immunotherapy and Immune Responses 8
- Aging top 2%
- Cell Biology top 1%
- Molecular Biology top 2%
- Muscle Physiology and Disorders 7
- Physiology top 2%
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- Cardiomyopathy and Myosin Studies 8
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- Mosquito-borne diseases and control 7
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- Influenza Virus Research Studies 6
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- Virus-based gene therapy research 6
- Co-authors
- Victor J. FerransToren FinkelZu‐Xi YuZu-Xi YuJonathan W. YewdellHeather D. HickmanJoel MossJack R. Bennink
- Cited by
- ImmunologyAgingCell Biology
- Journals
- Proceedings of the National Academy of Sciences (11 papers)PLoS ONE (9 papers)The Journal of Immunology (8 papers)
- Partner nations
- United StatesJapanAustralia
In The Last Decade
Kazuyo Takeda
113 papers receiving 6.4k citations
Hit Papers
Peers
Comparison fields: 5 of 139
- Immunology 1.4k
- Aging 90
- Cell Biology 769
- Molecular Biology 3.2k
- Physiology 1.1k
Countries citing papers authored by Kazuyo Takeda
This map shows the geographic impact of Kazuyo Takeda'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 Kazuyo Takeda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kazuyo Takeda more than expected).
Fields of papers citing papers by Kazuyo Takeda
This network shows the impact of papers produced by Kazuyo Takeda. 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 Kazuyo Takeda. The network helps show where Kazuyo Takeda may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Kazuyo Takeda, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 7 | |
| 3 | 2024 | 3 | |
| 4 | 2023 | 10 | |
| 5 | 2021 | 35 | |
| 6 | 2018 | 19 | |
| 7 | Wild Mouse Gut Microbiota Promotes Host Fitness and Improves Disease Resistancebreakdown → | 2017 | 571 |
| 8 | 2015 | 3 | |
| 9 | 2012 | 44 | |
| 10 | 2009 | 33 | |
| 11 | 2009 | 100 | |
| 12 | Skeletal myopathy and restrictive cardiomyopathy with atrioventricular conduction block resulting from desmin mutation | 2006 | 1 |
| 13 | 2002 | 8 | |
| 14 | 2002 | 71 | |
| 15 | 2000 | 5 | |
| 16 | 2000 | 100 | |
| 17 | 2000 | 77 | |
| 18 | 1998 | 129 | |
| 19 | 1996 | 31 | |
| 20 | 1995 | 2 |
About Kazuyo Takeda
Kazuyo Takeda is a scholar working on Immunology, Parasitology and Virology, having authored 116 papers that have together received 6.5k indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (10 papers), T-cell and B-cell Immunology (10 papers), Cardiomyopathy and Myosin Studies (8 papers), Immunotherapy and Immune Responses (8 papers), Muscle Physiology and Disorders (7 papers), Mosquito-borne diseases and control (7 papers), Influenza Virus Research Studies (6 papers) and Virus-based gene therapy research (6 papers). The work is most often cited by research in Immunology (1.4k citations), Aging (90 citations) and Cell Biology (769 citations). Kazuyo Takeda has collaborated with scholars based in United States, Japan and Australia. Frequent co-authors include Victor J. Ferrans, Toren Finkel, Zu‐Xi Yu, Zu‐Xi Yu, Zu-Xi Yu, Jonathan W. Yewdell, Heather D. Hickman, Joel Moss, Jack R. Bennink and Shino Nemoto. Their work appears in journals such as Proceedings of the National Academy of Sciences, PLoS ONE, The Journal of Immunology, Journal of Biological Chemistry and Archives of Pathology & Laboratory Medicine.
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.