Kanji Miyamoto
- Immunology top 5%
- Molecular Biology
- Ecology, Evolution, Behavior and Systematics top 2%
- Agronomy and Crop Science top 2%
- Cellular and Molecular Neuroscience top 10%
- Co-authors
- Shigeko NishimuraKaori KawakamiJiro SatoNoriko TomitaIkuro KimuraIsao MiyoshiKoichi KitajimaT Tsubota
- Topics
- T-cell and Retrovirus Studies (21 papers)Vector-Borne Animal Diseases (15 papers)Animal Disease Management and Epidemiology (14 papers)
- Partner nations
- JapanUnited StatesChile
In The Last Decade
Kanji Miyamoto
56 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 95
- Immunology 560
- Molecular Biology 386
- Ecology, Evolution, Behavior and Systematics 368
- Agronomy and Crop Science 365
- Cellular and Molecular Neuroscience 184
Countries citing papers authored by Kanji Miyamoto
This map shows the geographic impact of Kanji 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 Kanji Miyamoto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kanji Miyamoto more than expected).
Fields of papers citing papers by Kanji Miyamoto
This network shows the impact of papers produced by Kanji 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 Kanji Miyamoto. The network helps show where Kanji Miyamoto may publish in the future.
Co-authorship network of co-authors of Kanji Miyamoto
This figure shows the co-authorship network connecting the top 25 collaborators of Kanji Miyamoto. A scholar is included among the top collaborators of Kanji Miyamoto based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kanji Miyamoto. Kanji Miyamoto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 19 | |
| 2 | 14.Human placenta feeder layers support undifferentiated growth of primate embryonic stem cells(12th Annual Meeting of the Society of Hard Tissue Biology) | 8 |
| 3 | 14 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | 6 | |
| 7 | 33 | |
| 8 | 6 | |
| 9 | 4 | |
| 10 | 3 | |
| 11 | 2 | |
| 12 | 228 | |
| 13 | 12 | |
| 14 | 19 | |
| 15 | 10 | |
| 16 | 0 | |
| 17 | 3 | |
| 18 | 19 | |
| 19 | PHOSPHORUS METABOLISM IN HUMAN ERYTHROCYTE:II. SEPARATION OF ACID-SOLUBLE PHOSPHORUS COMPOUNDS INCORPORATING P 32 BY COLUMN CHROMATOGRAPHY WITH ION EXCHANGE RESIN | 9 |
| 20 | PHOPHORUS METABOLISM IN HUMAN ERYTHROCYTE:I. PAPER-CHROMATOGRAPHIC SEPARATION OF ACID-SOLUBLE PHOPHORUS COMPOUNDS INCORPORATING P | 28 |
About Kanji Miyamoto
Kanji Miyamoto is a scholar working on Agronomy and Crop Science, Immunology and Ecology, Evolution, Behavior and Systematics, having authored 58 papers that have together received 1.3k indexed citations. Recurring topics across this work include T-cell and Retrovirus Studies (21 papers), Vector-Borne Animal Diseases (15 papers) and Animal Disease Management and Epidemiology (14 papers). The work is most often cited by research in Agronomy and Crop Science (365 citations), Immunology (560 citations) and Ecology, Evolution, Behavior and Systematics (368 citations). Kanji Miyamoto has collaborated with scholars based in Japan, United States and Chile. Frequent co-authors include Shigeko Nishimura, Kaori Kawakami, Jiro Sato, Noriko Tomita, Ikuro Kimura, Isao Miyoshi, Koichi Kitajima, T Tsubota, Shunkichi Hiraki and Ichiro Kubonishi. Their work appears in journals such as JNCI Journal of the National Cancer Institute, Cancer and Brain Research.
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.