Mitsutoshi Yoneyama
- Immunology top 0.05%
- interferon and immune responses 67
- Immune Response and Inflammation 35
- Hepatology top 0.5%
- Hepatitis C virus research 8
- Infectious Diseases top 0.2%
- Cancer Research top 0.5%
- Animal Science and Zoology top 0.2%
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- RNA regulation and disease 23
- Inflammasome and immune disorders 12
- RNA Research and Splicing 8
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- Cytokine Signaling Pathways and Interactions 21
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- Neural Networks and Applications 9
Mitsutoshi Yoneyama
101 papers receiving 18.0k citations
Hit Papers
Peers
Comparison fields: 5 of 137
- Immunology 14.1k
- Hepatology 1.5k
- Infectious Diseases 3.4k
- Cancer Research 1.8k
- Animal Science and Zoology 1.2k
Countries citing papers authored by Mitsutoshi Yoneyama
This map shows the geographic impact of Mitsutoshi Yoneyama'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 Mitsutoshi Yoneyama with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mitsutoshi Yoneyama more than expected).
Fields of papers citing papers by Mitsutoshi Yoneyama
This network shows the impact of papers produced by Mitsutoshi Yoneyama. 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 Mitsutoshi Yoneyama. The network helps show where Mitsutoshi Yoneyama may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Mitsutoshi Yoneyama, 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 | 2023 | 16 | |
| 2 | Regulation of RIG-I-like receptor-mediated signaling: interaction between host and viral factorsbreakdown → | 2021 | 263 |
| 3 | 2016 | 46 | |
| 4 | 2016 | 68 | |
| 5 | 2014 | 38 | |
| 6 | 2014 | 127 | |
| 7 | 2013 | 19 | |
| 8 | 2012 | 52 | |
| 9 | 2012 | 124 | |
| 10 | 2012 | 11 | |
| 11 | 2011 | 20 | |
| 12 | LGP2 is a positive regulator of RIG-I– and MDA5-mediated antiviral responsesbreakdown → | 2010 | 519 |
| 13 | 2007 | 118 | |
| 14 | 2006 | 114 | |
| 15 | Regulating Intracellular Antiviral Defense and Permissiveness to Hepatitis C Virus RNA Replication through a Cellular RNA Helicase, RIG-Ibreakdown → | 2005 | 713 |
| 16 | 2005 | 447 | |
| 17 | Cell Type-Specific Involvement of RIG-I in Antiviral Responsebreakdown → | 2005 | 1104 |
| 18 | 2002 | 137 | |
| 19 | Facial Expressions Recognition Using Discrete Hopfield Neural Network | 1997 | 8 |
| 20 | 1996 | 122 |
About Mitsutoshi Yoneyama
Mitsutoshi Yoneyama is a scholar working on Immunology, Hepatology and Oncology, having authored 104 papers that have together received 18.3k indexed citations. Recurring topics across this work include interferon and immune responses (67 papers), Immune Response and Inflammation (35 papers), RNA regulation and disease (23 papers), Cytokine Signaling Pathways and Interactions (21 papers), Inflammasome and immune disorders (12 papers), Neural Networks and Applications (9 papers), Hepatitis C virus research (8 papers) and RNA Research and Splicing (8 papers). The work is most often cited by research in Immunology (14.1k citations), Hepatology (1.5k citations) and Infectious Diseases (3.4k citations). Mitsutoshi Yoneyama has collaborated with scholars based in Japan, United States and Poland. Frequent co-authors include Takashi Fujita, Shizuo Akira, Tadaatsu Imaizumi, Makoto Miyagishi, Mika Kikuchi, Kazunari Taira, Hiroki Kato, Noriaki Shinobu, Takashi Natsukawa and Koji Onomoto. Their work appears in journals such as Journal of Biological Chemistry, Journal of Virology, PLoS ONE, Immunity and Nucleic Acids 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.