Daisuke Shima
Impact in
- Hematology top 10%
- Acute Myeloid Leukemia Research
- Hematopoietic Stem Cell Transplantation
Papers in
-
- RNA Interference and Gene Delivery 2
- RNA Research and Splicing 2
- Genomics and Chromatin Dynamics 2
- Oncology 4
- Drug Transport and Resistance Mechanisms 2
- Co-authors
- Hiroshi Handa (7 shared papers)Yoko Fujimoto (7 shared papers)Masaki Hiramoto (5 shared papers)Shin Aizawa (5 shared papers)Tadashi Wada (2 shared papers)H Hoshi (2 shared papers)Toshimasa Osada (1 shared paper)T. Tsuchiya (1 shared paper)
- Journals
- Value in Health (4 papers)Cancer Chemotherapy and Pharmacology (2 papers)International Journal of Molecular Medicine (2 papers)Journal of Biological Chemistry (2 papers)Journal of Clinical Hypertension (2 papers)
- Partner nations
- JapanUnited StatesBelgium
In The Last Decade
Daisuke Shima
25 papers receiving 590 citations
Peers
Comparison fields: 5 of 81
- Hematology 90
- Nephrology 34
- Molecular Biology 255
- Genetics 34
- Rheumatology 46
Countries citing papers authored by Daisuke Shima
This map shows the geographic impact of Daisuke Shima'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 Shima with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daisuke Shima more than expected).
Fields of papers citing papers by Daisuke Shima
This network shows the impact of papers produced by Daisuke Shima. 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 Shima. The network helps show where Daisuke Shima may publish in the future.
Co-authors
The 25 scholars most cited alongside Daisuke Shima, 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 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2000 | 88 | |
| 2 | 1999 | 83 | |
| 3 | 1999 | 81 | |
| 4 | 2018 | 70 | |
| 5 | 2013 | 32 | |
| 6 | 2004 | 30 | |
| 7 | 2012 | 30 | |
| 8 | 2022 | 26 | |
| 9 | 2010 | 23 | |
| 10 | 2014 | 20 | |
| 11 | 2017 | 17 | |
| 12 | 2020 | 16 | |
| 13 | 2002 | 16 | |
| 14 | 2000 | 16 | |
| 15 | 2003 | 13 | |
| 16 | 2001 | 13 | |
| 17 | 2019 | 11 | |
| 18 | 2022 | 6 | |
| 19 | 2021 | 4 | |
| 20 | 2018 | 4 |
About Daisuke Shima
Daisuke Shima is a scholar working on Molecular Biology, Oncology, Endocrinology, Diabetes and Metabolism, Pharmacology and Cardiology and Cardiovascular Medicine, having authored 27 papers that have together received 606 indexed citations. Recurring topics across this work include Growth Hormone and Insulin-like Growth Factors (3 papers), Osteoarthritis Treatment and Mechanisms (2 papers), Inflammatory mediators and NSAID effects (2 papers), Drug Transport and Resistance Mechanisms (2 papers), RNA Interference and Gene Delivery (2 papers), RNA Research and Splicing (2 papers), Acute Myocardial Infarction Research (2 papers) and Genomics and Chromatin Dynamics (2 papers). The work is most often cited by research in Hematology (90 citations), Nephrology (34 citations), Molecular Biology (255 citations), Genetics (34 citations) and Rheumatology (46 citations). Daisuke Shima has collaborated with scholars based in Japan, United States and Belgium. Frequent co-authors include Hiroshi Handa, Yoko Fujimoto, Masaki Hiramoto, Shin Aizawa, Tadashi Wada, H Hoshi, Toshimasa Osada, T. Tsuchiya, Yuki Yamaguchi and Ken Nakata. Their work appears in journals such as Value in Health, Cancer Chemotherapy and Pharmacology, International Journal of Molecular Medicine, Journal of Biological Chemistry and Journal of Clinical Hypertension.
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.