Toshihiro Miyamoto
- Hematology top 0.05%
- Hematopoietic Stem Cell Transplantation 101
- Acute Myeloid Leukemia Research 85
- Chronic Myeloid Leukemia Treatments 38
- Multiple Myeloma Research and Treatments 32
- Immunology top 0.2%
- Immune Cell Function and Interaction 47
- T-cell and Retrovirus Studies 24
- Genetics top 0.5%
- Oncology top 0.5%
- Molecular Biology top 1%
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- Acute Lymphoblastic Leukemia research 40
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- Lymphoma Diagnosis and Treatment 29
- Co-authors
- Koichi AkashiIrving L. WeissmanDavid TraverHiromi IwasakiMine HaradaYoshikane KikushigeMarkus G. ManzKatsuto Takenaka
- Cited by
- HematologyImmunologyGenetics
- Journals
- Nature (2 papers)Science (1 paper)Proceedings of the National Academy of Sciences (5 papers)
- Partner nations
- JapanUnited StatesAustralia
In The Last Decade
Toshihiro Miyamoto
332 papers receiving 13.5k citations
Hit Papers
Peers
Comparison fields: 5 of 133
- Hematology 5.8k
- Immunology 6.0k
- Genetics 1.7k
- Oncology 3.2k
- Molecular Biology 4.2k
Countries citing papers authored by Toshihiro Miyamoto
This map shows the geographic impact of Toshihiro Miyamoto'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 Toshihiro Miyamoto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Toshihiro Miyamoto more than expected).
Fields of papers citing papers by Toshihiro Miyamoto
This network shows the impact of papers produced by Toshihiro Miyamoto. 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 Toshihiro Miyamoto. The network helps show where Toshihiro Miyamoto may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Toshihiro Miyamoto, 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 | 2024 | 2 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 1 | |
| 4 | 2023 | 2 | |
| 5 | 2022 | 0 | |
| 6 | 2022 | 5 | |
| 7 | 2022 | 1 | |
| 8 | 2022 | 1 | |
| 9 | 2022 | 8 | |
| 10 | 2021 | 0 | |
| 11 | 2021 | 2 | |
| 12 | 2020 | 0 | |
| 13 | 2020 | 0 | |
| 14 | 2020 | 2 | |
| 15 | 2019 | 62 | |
| 16 | 2019 | 8 | |
| 17 | 2017 | 15 | |
| 18 | 2016 | 20 | |
| 19 | 2009 | 200 | |
| 20 | 1996 | 43 |
About Toshihiro Miyamoto
Toshihiro Miyamoto is a scholar working on Hematology, Immunology and Genetics, having authored 359 papers that have together received 13.7k indexed citations. Recurring topics across this work include Hematopoietic Stem Cell Transplantation (101 papers), Acute Myeloid Leukemia Research (85 papers), Immune Cell Function and Interaction (47 papers), Acute Lymphoblastic Leukemia research (40 papers), Chronic Myeloid Leukemia Treatments (38 papers), Multiple Myeloma Research and Treatments (32 papers), Lymphoma Diagnosis and Treatment (29 papers) and T-cell and Retrovirus Studies (24 papers). The work is most often cited by research in Hematology (5.8k citations), Immunology (6.0k citations) and Genetics (1.7k citations). Toshihiro Miyamoto has collaborated with scholars based in Japan, United States and Australia. Frequent co-authors include Koichi Akashi, Irving L. Weissman, David Traver, Hiromi Iwasaki, Mine Harada, Yoshikane Kikushige, Markus G. Manz, Katsuto Takenaka, Koji Nagafuji and Goichi Yoshimoto. Their work appears in journals such as Nature, Science and Proceedings of the National Academy of Sciences.
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.