Yu Kato
- Immunology top 2%
- Immunotherapy and Immune Responses 8
- Immune Cell Function and Interaction 7
- T-cell and B-cell Immunology 5
- Immune cells in cancer 3
- Oncology top 1%
- Cancer Immunotherapy and Biomarkers 8
- Hepatology top 5%
- Cancer Research top 10%
- Cancer, Hypoxia, and Metabolism 5
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- Ferroptosis and cancer prognosis 5
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- Fibroblast Growth Factor Research 3
- Co-authors
- Tasuku HonjoTaku OkazakiTakanori KitamuraJeffrey W. PollardLuca CassettaKenji KabashimaMotonobu NakamuraHiroaki Yagi
- Cited by
- ImmunologyOncologyHepatology
- Journals
- The Journal of Experimental Medicine (2 papers)Journal of Clinical Oncology (1 paper)The Journal of Immunology (3 papers)
- Partner nations
- JapanUnited StatesUnited Kingdom
In The Last Decade
Yu Kato
27 papers receiving 2.7k citations
Hit Papers
Peers
Comparison fields: 5 of 93
- Immunology 1.5k
- Oncology 1.8k
- Hepatology 262
- Cancer Research 215
- Pathology and Forensic Medicine 249
Countries citing papers authored by Yu Kato
This map shows the geographic impact of Yu Kato'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 Yu Kato with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yu Kato more than expected).
Fields of papers citing papers by Yu Kato
This network shows the impact of papers produced by Yu Kato. 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 Yu Kato. The network helps show where Yu Kato may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Yu Kato, 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 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 1 | |
| 4 | 2023 | 1 | |
| 5 | 2021 | 5 | |
| 6 | 2021 | 6 | |
| 7 | 2019 | 14 | |
| 8 | Lenvatinib plus anti-PD-1 antibody combination treatment activates CD8+ T cells through reduction of tumor-associated macrophage and activation of the interferon pathwaybreakdown → | 2019 | 341 |
| 9 | 2018 | 119 | |
| 10 | 2016 | 33 | |
| 11 | 2016 | 26 | |
| 12 | 2015 | 54 | |
| 13 | 2015 | 13 | |
| 14 | 2014 | 32 | |
| 15 | PD-1 and LAG-3 inhibitory co-receptors act synergistically to prevent autoimmunity in micebreakdown → | 2011 | 255 |
| 16 | 2010 | 220 | |
| 17 | 2009 | 8 | |
| 18 | 2006 | 43 | |
| 19 | 2003 | 75 | |
| 20 | 2001 | 128 |
About Yu Kato
Yu Kato is a scholar working on Immunology, Oncology and Cancer Research, having authored 30 papers that have together received 2.7k indexed citations. Recurring topics across this work include Cancer Immunotherapy and Biomarkers (8 papers), Immunotherapy and Immune Responses (8 papers), Immune Cell Function and Interaction (7 papers), Cancer, Hypoxia, and Metabolism (5 papers), Ferroptosis and cancer prognosis (5 papers), T-cell and B-cell Immunology (5 papers), Fibroblast Growth Factor Research (3 papers) and Immune cells in cancer (3 papers). The work is most often cited by research in Immunology (1.5k citations), Oncology (1.8k citations) and Hepatology (262 citations). Yu Kato has collaborated with scholars based in Japan, United States and United Kingdom. Frequent co-authors include Tasuku Honjo, Taku Okazaki, Takanori Kitamura, Jeffrey W. Pollard, Luca Cassetta, Kenji Kabashima, Motonobu Nakamura, Hiroaki Yagi, Y. Tokura and Ryosuke Hino. Their work appears in journals such as The Journal of Experimental Medicine, Journal of Clinical Oncology and The Journal of Immunology.
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.