Daiki Ueno

779 total citations
23 papers, 432 citations indexed

About

Daiki Ueno is a scholar working on Pulmonary and Respiratory Medicine, Molecular Biology and Surgery. According to data from OpenAlex, Daiki Ueno has authored 23 papers receiving a total of 432 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Pulmonary and Respiratory Medicine, 8 papers in Molecular Biology and 5 papers in Surgery. Recurrent topics in Daiki Ueno's work include Renal cell carcinoma treatment (13 papers), Renal and related cancers (6 papers) and Cancer Genomics and Diagnostics (5 papers). Daiki Ueno is often cited by papers focused on Renal cell carcinoma treatment (13 papers), Renal and related cancers (6 papers) and Cancer Genomics and Diagnostics (5 papers). Daiki Ueno collaborates with scholars based in Japan, United States and China. Daiki Ueno's co-authors include Brian Shuch, Masahiro Yao, Kazuhide Makiyama, Noboru Nakaigawa, Ranjit S. Bindra, Marta Boeke, Xun Bao, Ranjini K. Sundaram, Yanfeng Liu and Yoshinobu Kubota and has published in prestigious journals such as Nature Genetics, SHILAP Revista de lepidopterología and Scientific Reports.

In The Last Decade

Daiki Ueno

21 papers receiving 430 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Daiki Ueno Japan 12 224 199 130 82 82 23 432
Jianwei Wang China 13 162 0.7× 344 1.7× 113 0.9× 81 1.0× 275 3.4× 46 659
Katherine J. Blair United States 11 138 0.6× 55 0.3× 84 0.6× 64 0.8× 67 0.8× 17 389
Giovanna Vacca Italy 11 157 0.7× 105 0.5× 68 0.5× 78 1.0× 209 2.5× 21 548
Reza Golestani United States 15 92 0.4× 165 0.8× 96 0.7× 95 1.2× 111 1.4× 27 444
Nozomu Kawata Japan 12 110 0.5× 247 1.2× 94 0.7× 91 1.1× 40 0.5× 28 397
Xiaolan Ruan China 13 107 0.5× 133 0.7× 64 0.5× 59 0.7× 26 0.3× 27 352
Fatiha Merabtene France 11 166 0.7× 86 0.4× 123 0.9× 184 2.2× 69 0.8× 20 509
Zongtai Zheng China 13 233 1.0× 176 0.9× 164 1.3× 128 1.6× 79 1.0× 37 504
Stephen Raskin Israel 10 243 1.1× 84 0.4× 146 1.1× 111 1.4× 83 1.0× 31 607

Countries citing papers authored by Daiki Ueno

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Daiki Ueno

This figure shows the co-authorship network connecting the top 25 collaborators of Daiki Ueno. A scholar is included among the top collaborators of Daiki Ueno based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Daiki Ueno. Daiki Ueno is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Tatenuma, Tomoyuki, Daiki Ueno, Yusuke Ito, et al.. (2025). Spinal CRH facilitates the micturition reflex via the CRH2 receptor in rats with normal bladder and bladder outlet obstruction. Scientific Reports. 15(1). 3604–3604. 2 indexed citations
2.
3.
Ito, Hiroki, Tomoyuki Tatenuma, Daiki Ueno, et al.. (2024). Tissue factor pathway inhibitor 2 (TFPI2) is a potential serum biomarker for clear cell renal carcinoma. Scientific Reports. 14(1). 28639–28639. 3 indexed citations
4.
5.
Wilde, Blake R., Daiki Ueno, Edward D. Esplin, et al.. (2023). FH Variant Pathogenicity Promotes Purine Salvage Pathway Dependence in Kidney Cancer. Cancer Discovery. 13(9). 2072–2089. 19 indexed citations
6.
Ito, Hiroki, et al.. (2022). Retrospective analysis of second-generation bipolar transurethral vaporization of the prostate in older patients aged ≥80 years with benign prostate enlargement. SHILAP Revista de lepidopterología. 2. 100034–100034. 2 indexed citations
7.
Ueno, Daiki, Juan C. Vasquez, Amrita Sule, et al.. (2022). Targeting Krebs-cycle-deficient renal cell carcinoma with Poly ADP-ribose polymerase inhibitors and low-dose alkylating chemotherapy. Oncotarget. 13(1). 1054–1067. 11 indexed citations
8.
McGillivray, Patrick D., Daiki Ueno, Aydin Pooli, et al.. (2020). Distinguishing Benign Renal Tumors with an Oncocytic Gene Expression (ONEX) Classifier. European Urology. 79(1). 107–111. 14 indexed citations
9.
Kang, Min, Kay Y. Chong, Tobias M.P. Hartwich, et al.. (2020). Ovarian BDNF promotes survival, migration, and attachment of tumor precursors originated from p53 mutant fallopian tube epithelial cells. Oncogenesis. 9(5). 55–55. 11 indexed citations
10.
Fujibuchi, Toshioh, et al.. (2019). Examination of Application to Radiation Protection Education by Four-dimensional Visualization of Scatter Distribution in Radiological Examination Using Virtual Reality. Japanese Journal of Radiological Technology. 75(11). 1297–1307. 9 indexed citations
11.
Chong, Kay Y., Min Kang, Francesca Garofalo, et al.. (2019). Inhibition of Heat Shock Protein 90 suppresses TWIST1 Transcription. Molecular Pharmacology. 96(2). 168–179. 18 indexed citations
12.
Ueno, Daiki, Zuoquan Xie, Marta Boeke, et al.. (2018). Genomic Heterogeneity and the Small Renal Mass. Clinical Cancer Research. 24(17). 4137–4144. 13 indexed citations
13.
Sulkowski, Parker L., Ranjini K. Sundaram, Sebastian Oeck, et al.. (2018). Krebs-cycle-deficient hereditary cancer syndromes are defined by defects in homologous-recombination DNA repair. Nature Genetics. 50(8). 1086–1092. 155 indexed citations
14.
Nakaigawa, Noboru, S. Tsutsumi, Daiki Ueno, et al.. (2018). Time-dependent change of relapse sites of renal cell carcinoma after curative surgery. European Urology Supplements. 17(2). e625–e627. 2 indexed citations
15.
Nakaigawa, Noboru, Keiichi Kondo, Daiki Ueno, et al.. (2017). The acceleration of glucose accumulation in renal cell carcinoma assessed by FDG PET/CT demonstrated acquisition of resistance to tyrosine kinase inhibitor therapy. BMC Cancer. 17(1). 39–39. 18 indexed citations
16.
Minamimoto, Ryogo, Noboru Nakaigawa, Yoji Nagashima, et al.. (2016). Comparison of 11C-4DST and 18F-FDG PET/CT imaging for advanced renal cell carcinoma: preliminary study. Abdominal Radiology. 41(3). 521–530. 10 indexed citations
17.
Nakaigawa, Noboru, Keiichi Kondo, Ukihide Tateishi, et al.. (2016). FDG PET/CT as a prognostic biomarker in the era of molecular-targeting therapies: max SUVmax predicts survival of patients with advanced renal cell carcinoma. BMC Cancer. 16(1). 67–67. 36 indexed citations
18.
Makiyama, Kazuhide, Hiroyuki Yamanaka, Daiki Ueno, et al.. (2016). Comparison of the performance of experienced and novice surgeons: measurement of gripping force during laparoscopic surgery performed on pigs using forceps with pressure sensors. Surgical Endoscopy. 31(4). 1999–2005. 16 indexed citations
19.
Ueno, Daiki, Kazuhide Makiyama, Hiroyuki Yamanaka, et al.. (2014). Prediction of open urinary tract in laparoscopic partial nephrectomy by virtual resection plane visualization. BMC Urology. 14(1). 47–47. 8 indexed citations
20.
Ueno, Daiki, Masahiro Yao, Ukihide Tateishi, et al.. (2012). Early assessment by FDG-PET/CT of patients with advanced renal cell carcinoma treated with tyrosine kinase inhibitors is predictive of disease course. BMC Cancer. 12(1). 162–162. 55 indexed citations

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.

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