Shigeki Takemoto
- Immunology top 2%
- Ecology, Evolution, Behavior and Systematics top 1%
- Agronomy and Crop Science top 1%
- Oncology top 10%
- Molecular Biology
- Co-authors
- Genoveffa FranchiniMasao MatsuokaChristophe NicotRenaud MahieuxThomas A. WaldmannAnna CeresetoHitoshi SuzushimaAtae Utsunomiya
- Topics
- T-cell and Retrovirus Studies (39 papers)Vector-Borne Animal Diseases (28 papers)Animal Disease Management and Epidemiology (19 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of Clinical OncologySHILAP Revista de lepidopterología
- Partner nations
- JapanUnited StatesUnited Kingdom
In The Last Decade
Shigeki Takemoto
42 papers receiving 1.6k citations
Hit Papers
Peers
Comparison fields: 5 of 82
- Immunology 1.2k
- Ecology, Evolution, Behavior and Systematics 666
- Agronomy and Crop Science 573
- Oncology 363
- Molecular Biology 347
Countries citing papers authored by Shigeki Takemoto
This map shows the geographic impact of Shigeki Takemoto'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 Shigeki Takemoto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shigeki Takemoto more than expected).
Fields of papers citing papers by Shigeki Takemoto
This network shows the impact of papers produced by Shigeki Takemoto. 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 Shigeki Takemoto. The network helps show where Shigeki Takemoto may publish in the future.
Co-authorship network of co-authors of Shigeki Takemoto
This figure shows the co-authorship network connecting the top 25 collaborators of Shigeki Takemoto. A scholar is included among the top collaborators of Shigeki Takemoto 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 Shigeki Takemoto. Shigeki Takemoto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 52 | |
| 2 | 0 | |
| 3 | 9 | |
| 4 | 0 | |
| 5 | 6 | |
| 6 | 1 | |
| 7 | 57 | |
| 8 | 38 | |
| 9 | 4 | |
| 10 | 7 | |
| 11 | 4 | |
| 12 | 2 | |
| 13 | 22 | |
| 14 | 18 | |
| 15 | 3 | |
| 16 | 15 | |
| 17 | HTLV-I provirus in the clinical subtypes of ATL. | 9 |
| 18 | 29 | |
| 19 | 2 | |
| 20 | Establishment of a CD45-positive immature plasma cell line from an aggressive multiple myeloma with high serum lactate dehydrogenase. | 28 |
About Shigeki Takemoto
Shigeki Takemoto is a scholar working on Agronomy and Crop Science, Immunology and Ecology, Evolution, Behavior and Systematics, having authored 49 papers that have together received 1.6k indexed citations. Recurring topics across this work include T-cell and Retrovirus Studies (39 papers), Vector-Borne Animal Diseases (28 papers) and Animal Disease Management and Epidemiology (19 papers). The work is most often cited by research in Agronomy and Crop Science (573 citations), Immunology (1.2k citations) and Ecology, Evolution, Behavior and Systematics (666 citations). Shigeki Takemoto has collaborated with scholars based in Japan, United States and United Kingdom. Frequent co-authors include Genoveffa Franchini, Masao Matsuoka, Christophe Nicot, Renaud Mahieux, Thomas A. Waldmann, Anna Cereseto, Hitoshi Suzushima, Atae Utsunomiya, Shinichiro Yoshida and Kazuhito Yamamoto. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.
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.