Shinya Kimura
- Hematology top 0.2%
- Chronic Myeloid Leukemia Treatments 129
- Acute Myeloid Leukemia Research 38
- Genetics top 0.5%
- Chronic Lymphocytic Leukemia Research 91
- Oncology top 1%
- Immunology top 2%
- T-cell and Retrovirus Studies 21
- Cancer Research top 2%
- Cancer Genomics and Diagnostics 20
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- Eosinophilic Disorders and Syndromes 54
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- Lung Cancer Treatments and Mutations 31
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- Lymphoma Diagnosis and Treatment 28
- Co-authors
- Taira MaekawaJunya KurodaEishi AshiharaTakeshi YuasaNaoko Sueoka‐AraganeAndrew W. RobertsAsumi YokotaHiroshi Nojima
- Cited by
- HematologyGeneticsOncology
- Partner nations
- JapanUnited StatesAustralia
In The Last Decade
Shinya Kimura
405 papers receiving 6.9k citations
Peers
Comparison fields: 5 of 155
- Hematology 2.1k
- Genetics 1.3k
- Oncology 2.1k
- Immunology 998
- Cancer Research 683
Countries citing papers authored by Shinya Kimura
This map shows the geographic impact of Shinya Kimura'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 Shinya Kimura with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shinya Kimura more than expected).
Fields of papers citing papers by Shinya Kimura
This network shows the impact of papers produced by Shinya Kimura. 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 Shinya Kimura. The network helps show where Shinya Kimura may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Shinya Kimura, 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 | 2024 | 1 | |
| 2 | 2024 | 0 | |
| 3 | 2023 | 3 | |
| 4 | 2023 | 1 | |
| 5 | Anti-IL-5 Agents for the Treatment of Idiopathic Chronic Eosinophilic Pneumonia: A Case Series | 2022 | 8 |
| 6 | 2022 | 6 | |
| 7 | 2020 | 13 | |
| 8 | 2020 | 4 | |
| 9 | 2018 | 26 | |
| 10 | 2018 | 1 | |
| 11 | 2018 | 9 | |
| 12 | 2016 | 24 | |
| 13 | 2015 | 20 | |
| 14 | 2014 | 9 | |
| 15 | 2013 | 35 | |
| 16 | 2010 | 61 | |
| 17 | 2009 | 41 | |
| 18 | 2008 | 47 | |
| 19 | Overcoming imatinib resistance using Src inhibitor CGP76030, Abl inhibitor nilotinib, and Abl/Lyn inhibitor INNO-406 in newly established K562 variants with bcr-abl gene amplification. | 2007 | 3 |
| 20 | 2005 | 165 |
About Shinya Kimura
Shinya Kimura is a scholar working on Hematology, Genetics and Rheumatology, having authored 427 papers that have together received 7.1k indexed citations. Recurring topics across this work include Chronic Myeloid Leukemia Treatments (129 papers), Chronic Lymphocytic Leukemia Research (91 papers), Eosinophilic Disorders and Syndromes (54 papers), Acute Myeloid Leukemia Research (38 papers), Lung Cancer Treatments and Mutations (31 papers), Lymphoma Diagnosis and Treatment (28 papers), T-cell and Retrovirus Studies (21 papers) and Cancer Genomics and Diagnostics (20 papers). The work is most often cited by research in Hematology (2.1k citations), Genetics (1.3k citations) and Oncology (2.1k citations). Shinya Kimura has collaborated with scholars based in Japan, United States and Australia. Frequent co-authors include Taira Maekawa, Junya Kuroda, Eishi Ashihara, Takeshi Yuasa, Naoko Sueoka‐Aragane, Andrew W. Roberts, Asumi Yokota, Hiroshi Nojima, Hidekazu Segawa and Donald Metcalf. Their work appears in journals such as Blood, International Journal of Hematology, PLoS ONE, Cancer Science and Cancer Letters.
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.