Takanori Ueda
- Hematology top 1%
- Acute Myeloid Leukemia Research 50
- Chronic Myeloid Leukemia Treatments 21
- Nephrology top 2%
- Genetics top 5%
- Chronic Lymphocytic Leukemia Research 28
- Oncology top 5%
- Molecular Biology top 5%
- Cancer therapeutics and mechanisms 19
- Biochemical and Molecular Research 18
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- Acute Lymphoblastic Leukemia research 32
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- Lymphoma Diagnosis and Treatment 20
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- Cardiac Imaging and Diagnostics 17
- Co-authors
- Akira YoshidaJong‐Dae LeeHiromichi IwasakiTakahiro YamauchiHiroyasu UzuiHiromasa ShimizuYoshimasa UrasakiSatoshi Ikegaya
- Cited by
- HematologyNephrologyGenetics
- Partner nations
- JapanChinaUnited States
In The Last Decade
Takanori Ueda
294 papers receiving 3.9k citations
Peers
Comparison fields: 5 of 148
- Hematology 675
- Nephrology 238
- Genetics 345
- Oncology 642
- Molecular Biology 1.5k
Countries citing papers authored by Takanori Ueda
This map shows the geographic impact of Takanori Ueda'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 Takanori Ueda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Takanori Ueda more than expected).
Fields of papers citing papers by Takanori Ueda
This network shows the impact of papers produced by Takanori Ueda. 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 Takanori Ueda. The network helps show where Takanori Ueda may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Takanori Ueda, 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 | 2 | |
| 2 | 2022 | 1 | |
| 3 | 2016 | 10 | |
| 4 | 2016 | 7 | |
| 5 | 2014 | 5 | |
| 6 | Low Latency Data Stream Processing on Multi-Core CPU Environments | 2013 | 0 |
| 7 | Early relapse is associated with high serum soluble interleukin-2 receptor after the sixth cycle of R-CHOP chemotherapy in patients with advanced diffuse large B-cell lymphoma. | 2012 | 13 |
| 8 | 2012 | 1 | |
| 9 | 2012 | 0 | |
| 10 | 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 |
| 11 | Copyright violation detection system for Web texts | 2006 | 0 |
| 12 | New quantitation method for monitoring cytarabine incorporated into DNA of leukemic cells from patients receiving cytarabine therapy | 2004 | 0 |
| 13 | 2004 | 73 | |
| 14 | 2003 | 6 | |
| 15 | 2002 | 65 | |
| 16 | 2001 | 10 | |
| 17 | 1998 | 1 | |
| 18 | 1998 | 14 | |
| 19 | 1996 | 2 | |
| 20 | 1989 | 2 |
About Takanori Ueda
Takanori Ueda is a scholar working on Hematology, Genetics and Nephrology, having authored 310 papers that have together received 4.1k indexed citations. Recurring topics across this work include Acute Myeloid Leukemia Research (50 papers), Acute Lymphoblastic Leukemia research (32 papers), Chronic Lymphocytic Leukemia Research (28 papers), Chronic Myeloid Leukemia Treatments (21 papers), Lymphoma Diagnosis and Treatment (20 papers), Cancer therapeutics and mechanisms (19 papers), Biochemical and Molecular Research (18 papers) and Cardiac Imaging and Diagnostics (17 papers). The work is most often cited by research in Hematology (675 citations), Nephrology (238 citations) and Genetics (345 citations). Takanori Ueda has collaborated with scholars based in Japan, China and United States. Frequent co-authors include Akira Yoshida, Jong‐Dae Lee, Hiromichi Iwasaki, Takahiro Yamauchi, Hiroyasu Uzui, Hiromasa Shimizu, Yoshimasa Urasaki, Satoshi Ikegaya, Yasuhiko Mitsuke and Tõru Nakamura. Their work appears in journals such as The Lancet, Journal of Biological Chemistry and Circulation.
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.