Daisuke Ohshima
Impact in
- Immunology top 10%
- T-cell and B-cell Immunology
- Immune Cell Function and Interaction
- Immunotherapy and Immune Responses
- Immune Response and Inflammation
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- NF-κB Signaling Pathways
Papers in
- Immunology 11
- Immune Response and Inflammation 6
- Immune Cell Function and Interaction 4
- Immunotherapy and Immune Responses 3
- T-cell and B-cell Immunology 3
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- NF-κB Signaling Pathways 8
- Co-authors
- Jun‐ichiro Inoue (8 shared papers)Hiromi Yanai (6 shared papers)Yusuke Shimo (6 shared papers)Taishin Akiyama (7 shared papers)Junwen Qin (6 shared papers)Yuya Maruyama (2 shared papers)Mitsuru Matsumoto (3 shared papers)Takeshi Nitta (2 shared papers)
In The Last Decade
Daisuke Ohshima
28 papers receiving 800 citations
Peers
Comparison fields: 5 of 80
- Immunology 444
- Cancer Research 145
- Oncology 197
- Endocrinology, Diabetes and Metabolism 108
- Endocrine and Autonomic Systems 23
Countries citing papers authored by Daisuke Ohshima
This map shows the geographic impact of Daisuke Ohshima'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 Daisuke Ohshima with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daisuke Ohshima more than expected).
Fields of papers citing papers by Daisuke Ohshima
This network shows the impact of papers produced by Daisuke Ohshima. 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 Daisuke Ohshima. The network helps show where Daisuke Ohshima may publish in the future.
Co-authors
The 25 scholars most cited alongside Daisuke Ohshima, 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 29 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2008 | 426 | |
| 2 | 2021 | 92 | |
| 3 | 2014 | 60 | |
| 4 | 2021 | 36 | |
| 5 | 2011 | 32 | |
| 6 | 2017 | 29 | |
| 7 | 2004 | 24 | |
| 8 | 2007 | 18 | |
| 9 | 2015 | 14 | |
| 10 | 2011 | 13 | |
| 11 | 2022 | 12 | |
| 12 | 2012 | 11 | |
| 13 | 2014 | 7 | |
| 14 | 2014 | 6 | |
| 15 | 2021 | 6 | |
| 16 | 2009 | 6 | |
| 17 | 2009 | 5 | |
| 18 | 2023 | 5 | |
| 19 | 2009 | 3 | |
| 20 | 2010 | 2 |
About Daisuke Ohshima
Daisuke Ohshima is a scholar working on Immunology, Cancer Research, Electrical and Electronic Engineering, Molecular Biology and Endocrinology, Diabetes and Metabolism, having authored 29 papers that have together received 818 indexed citations. Recurring topics across this work include NF-κB Signaling Pathways (8 papers), 3D IC and TSV technologies (7 papers), Electronic Packaging and Soldering Technologies (7 papers), Immune Response and Inflammation (6 papers), Immune Cell Function and Interaction (4 papers), Electromagnetic Compatibility and Noise Suppression (3 papers), Immunotherapy and Immune Responses (3 papers) and T-cell and B-cell Immunology (3 papers). The work is most often cited by research in Immunology (444 citations), Cancer Research (145 citations), Oncology (197 citations), Endocrinology, Diabetes and Metabolism (108 citations) and Endocrine and Autonomic Systems (23 citations). Daisuke Ohshima has collaborated with scholars based in Japan, China and Austria. Frequent co-authors include Jun‐ichiro Inoue, Hiromi Yanai, Yusuke Shimo, Taishin Akiyama, Junwen Qin, Yuya Maruyama, Mitsuru Matsumoto, Takeshi Nitta, Josef Martin Penninger and Yousuke Takahama. Their work appears in journals such as PLoS ONE, IEEE Transactions on Components Packaging and Manufacturing Technology, International Immunology, Immunity 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.