Mamoru Ito
- Immunology top 0.5%
- Immune Cell Function and Interaction 53
- T-cell and B-cell Immunology 37
- Immunotherapy and Immune Responses 26
- Virology top 0.5%
- HIV Research and Treatment 16
- Hematology top 0.5%
- Hematopoietic Stem Cell Transplantation 29
- Genetics top 1%
- Virus-based gene therapy research 13
- Oncology top 1%
- CAR-T cell therapy research 22
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- Pluripotent Stem Cells Research 13
- Co-authors
- Tatsutoshi NakahataKimio KobayashiYoshio KoyanagiRyoji ItoIkumi KatanoKohichiro TsujiTakeshi TakahashiKazutomo Suzue
- Cited by
- ImmunologyVirologyHematology
- Journals
- Blood (19 papers)EXPERIMENTAL ANIMALS (10 papers)Biochemical and Biophysical Research Communications (8 papers)
- Partner nations
- JapanUnited StatesChina
In The Last Decade
Mamoru Ito
216 papers receiving 9.8k citations
Hit Papers
Peers
Comparison fields: 5 of 141
- Immunology 4.1k
- Virology 827
- Hematology 1.6k
- Genetics 924
- Oncology 1.9k
Countries citing papers authored by Mamoru Ito
This map shows the geographic impact of Mamoru Ito'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 Mamoru Ito with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mamoru Ito more than expected).
Fields of papers citing papers by Mamoru Ito
This network shows the impact of papers produced by Mamoru Ito. 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 Mamoru Ito. The network helps show where Mamoru Ito may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Mamoru Ito, 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 | 2022 | 18 | |
| 2 | 2021 | 1 | |
| 3 | 2021 | 34 | |
| 4 | 2020 | 82 | |
| 5 | 2020 | 11 | |
| 6 | 2019 | 14 | |
| 7 | 2016 | 77 | |
| 8 | 2016 | 16 | |
| 9 | 2010 | 24 | |
| 10 | 2008 | 35 | |
| 11 | 2007 | 119 | |
| 12 | 2003 | 89 | |
| 13 | 2003 | 12 | |
| 14 | 2001 | 34 | |
| 15 | 2001 | 54 | |
| 16 | 2001 | 24 | |
| 17 | 2000 | 108 | |
| 18 | Key characters for the microscopical identification of Cylicocyclus nassatus and Cylicocyclus ashworthi (Nematoda: Cyathostominae) of the horse, Equus caballus | 1997 | 27 |
| 19 | Role of CD4⁺ T Cells in the Control of Primary Infection with Babesia microti in Mice | 1994 | 17 |
| 20 | 1985 | 2 |
About Mamoru Ito
Mamoru Ito is a scholar working on Immunology, Hematology and Virology, having authored 220 papers that have together received 10.0k indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (53 papers), T-cell and B-cell Immunology (37 papers), Hematopoietic Stem Cell Transplantation (29 papers), Immunotherapy and Immune Responses (26 papers), CAR-T cell therapy research (22 papers), HIV Research and Treatment (16 papers), Virus-based gene therapy research (13 papers) and Pluripotent Stem Cells Research (13 papers). The work is most often cited by research in Immunology (4.1k citations), Virology (827 citations) and Hematology (1.6k citations). Mamoru Ito has collaborated with scholars based in Japan, United States and China. Frequent co-authors include Tatsutoshi Nakahata, Kimio Kobayashi, Yoshio Koyanagi, Ryoji Ito, Ikumi Katano, Kohichiro Tsuji, Takeshi Takahashi, Kazutomo Suzue, Hidefumi Hiramatsu and Toshio Heike. Their work appears in journals such as Blood, EXPERIMENTAL ANIMALS, Biochemical and Biophysical Research Communications, Immunology Letters and Journal of Virology.
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.