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 10
- Immune Response and Inflammation 6
- Immune Cell Function and Interaction 4
- T-cell and B-cell Immunology 3
- Immunotherapy and Immune Responses 3
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- 3D IC and TSV technologies 7
- Electronic Packaging and Soldering Technologies 7
- Co-authors
- Jun‐ichiro Inoue (8 shared papers)Taishin Akiyama (7 shared papers)Yusuke Shimo (6 shared papers)Hiromi Yanai (6 shared papers)Junwen Qin (6 shared papers)Yuya Maruyama (2 shared papers)Mitsuru Matsumoto (3 shared papers)Hiroshi Takayanagi (1 shared paper)
In The Last Decade
Daisuke Ohshima
27 papers receiving 694 citations
Peers
Comparison fields: 5 of 75
- Immunology 397
- Cancer Research 129
- Endocrinology, Diabetes and Metabolism 108
- Oncology 156
- 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 28 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2008 | 413 | |
| 2 | 2014 | 55 | |
| 3 | 2021 | 35 | |
| 4 | 2011 | 31 | |
| 5 | 2017 | 28 | |
| 6 | 2004 | 23 | |
| 7 | 2007 | 19 | |
| 8 | 2015 | 15 | |
| 9 | 2011 | 13 | |
| 10 | 2012 | 11 | |
| 11 | 2022 | 11 | |
| 12 | 2014 | 7 | |
| 13 | 2014 | 6 | |
| 14 | 2009 | 6 | |
| 15 | 2021 | 6 | |
| 16 | 2023 | 5 | |
| 17 | 2009 | 5 | |
| 18 | 2009 | 3 | |
| 19 | 2010 | 2 | |
| 20 | 2015 | 2 |
About Daisuke Ohshima
Daisuke Ohshima is a scholar working on Immunology, Electrical and Electronic Engineering, Cancer Research, Molecular Biology and Mechanical Engineering, having authored 28 papers that have together received 705 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), T-cell and B-cell Immunology (3 papers), RNA Research and Splicing (3 papers) and Immunotherapy and Immune Responses (3 papers). The work is most often cited by research in Immunology (397 citations), Cancer Research (129 citations), Endocrinology, Diabetes and Metabolism (108 citations), Oncology (156 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, Taishin Akiyama, Yusuke Shimo, Hiromi Yanai, Junwen Qin, Yuya Maruyama, Mitsuru Matsumoto, Hiroshi Takayanagi, Yousuke Takahama and Takeshi Nitta. Their work appears in journals such as PLoS ONE, International Immunology, IEEE Transactions on Components Packaging and Manufacturing Technology, 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.