Rikako Tabata
Impact in
- Hematology top 10%
- Multiple Myeloma Research and Treatments
- Acute Myeloid Leukemia Research
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- CAR-T cell therapy research
- Peptidase Inhibition and Analysis
Papers in
- Hematology 21
- Multiple Myeloma Research and Treatments 17
- Hematopoietic Stem Cell Transplantation 3
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- Lymphoma Diagnosis and Treatment 8
- Co-authors
- Kosei Matsue (31 shared papers)Masami Takeuchi (33 shared papers)Kentaro Narita (34 shared papers)Yosuke Minami (1 shared paper)SungGi Chi (1 shared paper)Junichiro Yuda (1 shared paper)Toshiki Terao (21 shared papers)Daisuke Miura (21 shared papers)
- Journals
- Blood (9 papers)International Journal of Hematology (4 papers)British Journal of Haematology (3 papers)Blood Advances (2 papers)Scientific Reports (2 papers)
- Partner nations
- Japan
In The Last Decade
Rikako Tabata
33 papers receiving 199 citations
Peers
Comparison fields: 5 of 35
- Hematology 87
- Oncology 78
- Immunology 42
- Infectious Diseases 35
- Genetics 16
Countries citing papers authored by Rikako Tabata
This map shows the geographic impact of Rikako Tabata'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 Rikako Tabata with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rikako Tabata more than expected).
Fields of papers citing papers by Rikako Tabata
This network shows the impact of papers produced by Rikako Tabata. 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 Rikako Tabata. The network helps show where Rikako Tabata may publish in the future.
Co-authors
The 24 scholars most cited alongside Rikako Tabata, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 54 | |
| 2 | 2021 | 16 | |
| 3 | 2021 | 13 | |
| 4 | 2022 | 13 | |
| 5 | 2022 | 12 | |
| 6 | 2021 | 10 | |
| 7 | 2022 | 9 | |
| 8 | 2022 | 9 | |
| 9 | 2024 | 7 | |
| 10 | 2021 | 6 | |
| 11 | 2022 | 6 | |
| 12 | 2022 | 6 | |
| 13 | 2021 | 4 | |
| 14 | 2022 | 4 | |
| 15 | 2021 | 3 | |
| 16 | 2023 | 3 | |
| 17 | 2022 | 3 | |
| 18 | 2024 | 3 | |
| 19 | 2024 | 2 | |
| 20 | 2023 | 2 |
About Rikako Tabata
Rikako Tabata is a scholar working on Hematology, Pathology and Forensic Medicine, Immunology, Molecular Biology and Oncology, having authored 36 papers that have together received 203 indexed citations. Recurring topics across this work include Multiple Myeloma Research and Treatments (17 papers), Lymphoma Diagnosis and Treatment (8 papers), Monoclonal and Polyclonal Antibodies Research (4 papers), SARS-CoV-2 and COVID-19 Research (4 papers), Immunotherapy and Immune Responses (4 papers), Protein Degradation and Inhibitors (3 papers), Hematopoietic Stem Cell Transplantation (3 papers) and CNS Lymphoma Diagnosis and Treatment (3 papers). The work is most often cited by research in Hematology (87 citations), Oncology (78 citations), Immunology (42 citations), Infectious Diseases (35 citations) and Genetics (16 citations). Rikako Tabata has collaborated with scholars based in Japan. Frequent co-authors include Kosei Matsue, Masami Takeuchi, Kentaro Narita, Yosuke Minami, SungGi Chi, Junichiro Yuda, Toshiki Terao, Daisuke Miura, Daisuke Ikeda and Youichi Machida. Their work appears in journals such as Blood, International Journal of Hematology, British Journal of Haematology, Blood Advances and Scientific Reports.
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.