Daiki Ueno
Impact in
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- Cancer, Hypoxia, and Metabolism
- Cancer Genomics and Diagnostics
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- Renal cell carcinoma treatment
Papers in
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- Renal cell carcinoma treatment 13
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- Renal and related cancers 6
- Co-authors
- Brian Shuch (7 shared papers)Masahiro Yao (7 shared papers)Kazuhide Makiyama (10 shared papers)Ranjini K. Sundaram (2 shared papers)Marta Boeke (2 shared papers)Xun Bao (2 shared papers)Noboru Nakaigawa (8 shared papers)Ranjit S. Bindra (2 shared papers)
- Journals
- BMC Cancer (4 papers)Scientific Reports (2 papers)International Journal of Urology (2 papers)Clinical Cancer Research (1 paper)Nature Genetics (1 paper)
- Partner nations
- JapanUnited StatesChina
In The Last Decade
Daiki Ueno
21 papers receiving 430 citations
Peers
Comparison fields: 5 of 73
- Cancer Research 130
- Pulmonary and Respiratory Medicine 199
- Radiology, Nuclear Medicine and Imaging 82
- Molecular Biology 224
- Oncology 79
Countries citing papers authored by Daiki Ueno
This map shows the geographic impact of Daiki Ueno'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 Daiki Ueno with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daiki Ueno more than expected).
Fields of papers citing papers by Daiki Ueno
This network shows the impact of papers produced by Daiki Ueno. 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 Daiki Ueno. The network helps show where Daiki Ueno may publish in the future.
Co-authors
The 25 scholars most cited alongside Daiki Ueno, 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 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 155 | |
| 2 | 2012 | 55 | |
| 3 | 2016 | 36 | |
| 4 | 2023 | 19 | |
| 5 | 2019 | 18 | |
| 6 | 2017 | 18 | |
| 7 | 2015 | 17 | |
| 8 | 2016 | 16 | |
| 9 | 2020 | 14 | |
| 10 | 2018 | 13 | |
| 11 | 2014 | 12 | |
| 12 | 2022 | 11 | |
| 13 | 2020 | 11 | |
| 14 | 2016 | 10 | |
| 15 | 2019 | 9 | |
| 16 | 2014 | 8 | |
| 17 | 2024 | 3 | |
| 18 | 2022 | 2 | |
| 19 | 2025 | 2 | |
| 20 | 2018 | 2 |
About Daiki Ueno
Daiki Ueno is a scholar working on Pulmonary and Respiratory Medicine, Molecular Biology, Surgery, Oncology and Cancer Research, having authored 23 papers that have together received 432 indexed citations. Recurring topics across this work include Renal cell carcinoma treatment (13 papers), Renal and related cancers (6 papers), Cancer Genomics and Diagnostics (5 papers), MRI in cancer diagnosis (3 papers), Anatomy and Medical Technology (2 papers), Urinary Bladder and Prostate Research (2 papers), Bladder and Urothelial Cancer Treatments (2 papers) and PARP inhibition in cancer therapy (2 papers). The work is most often cited by research in Cancer Research (130 citations), Pulmonary and Respiratory Medicine (199 citations), Radiology, Nuclear Medicine and Imaging (82 citations), Molecular Biology (224 citations) and Oncology (79 citations). Daiki Ueno has collaborated with scholars based in Japan, United States and China. Frequent co-authors include Brian Shuch, Masahiro Yao, Kazuhide Makiyama, Ranjini K. Sundaram, Marta Boeke, Xun Bao, Noboru Nakaigawa, Ranjit S. Bindra, Yoshinobu Kubota and Yanfeng Liu. Their work appears in journals such as BMC Cancer, Scientific Reports, International Journal of Urology, Clinical Cancer Research and Nature Genetics.
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.