Hiroki Ueda

5.2k total citations
27 papers, 877 citations indexed

About

Hiroki Ueda is a scholar working on Molecular Biology, Cancer Research and Surgery. According to data from OpenAlex, Hiroki Ueda has authored 27 papers receiving a total of 877 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Molecular Biology, 9 papers in Cancer Research and 3 papers in Surgery. Recurrent topics in Hiroki Ueda's work include RNA modifications and cancer (8 papers), RNA regulation and disease (7 papers) and RNA Research and Splicing (6 papers). Hiroki Ueda is often cited by papers focused on RNA modifications and cancer (8 papers), RNA regulation and disease (7 papers) and RNA Research and Splicing (6 papers). Hiroki Ueda collaborates with scholars based in Japan, United States and Russia. Hiroki Ueda's co-authors include Tsutomu Suzuki, Masayuki Sakurai, Takanori Yano, Hitomi Kawabata, Shunpei Okada, Takeo Suzuki, Kenjyo Miyauchi, Yuriko Sakaguchi, Shogo Yamamoto and Asao Fujiyama and has published in prestigious journals such as Nature Biotechnology, Cancer Research and Scientific Reports.

In The Last Decade

Hiroki Ueda

26 papers receiving 866 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hiroki Ueda Japan 11 720 167 115 71 70 27 877
Vahid Marmari Iran 6 492 0.7× 181 1.1× 42 0.4× 36 0.5× 16 0.2× 10 630
Dang Hoang Lam Singapore 10 391 0.5× 202 1.2× 24 0.2× 40 0.6× 25 0.4× 12 577
Sarah A. Compton United States 13 742 1.0× 72 0.4× 123 1.1× 106 1.5× 32 0.5× 16 906
Bradley W. McLean Canada 8 343 0.5× 106 0.6× 130 1.1× 134 1.9× 39 0.6× 8 652
Michael Rutenberg-Schoenberg United States 8 769 1.1× 347 2.1× 54 0.5× 128 1.8× 30 0.4× 9 979
José L. Gutiérrez Chile 15 1.0k 1.4× 70 0.4× 138 1.2× 107 1.5× 14 0.2× 33 1.1k
Mehmet Fatih Bolukbasi United States 7 790 1.1× 337 2.0× 41 0.4× 71 1.0× 9 0.1× 7 820
Jinsong Yang China 13 271 0.4× 79 0.5× 17 0.1× 82 1.2× 58 0.8× 27 461
Alice Tanner United States 9 608 0.8× 172 1.0× 18 0.2× 219 3.1× 23 0.3× 11 797

Countries citing papers authored by Hiroki Ueda

Since Specialization
Citations

This map shows the geographic impact of Hiroki 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 Hiroki Ueda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hiroki Ueda more than expected).

Fields of papers citing papers by Hiroki Ueda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hiroki 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 Hiroki Ueda. The network helps show where Hiroki Ueda may publish in the future.

Co-authorship network of co-authors of Hiroki Ueda

This figure shows the co-authorship network connecting the top 25 collaborators of Hiroki Ueda. A scholar is included among the top collaborators of Hiroki Ueda 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 Hiroki Ueda. Hiroki Ueda 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.
Yu, Boyi, Genta Nagae, Yutaka Midorikawa, et al.. (2024). m6ATM: a deep learning framework for demystifying the m6A epitranscriptome with Nanopore long-read RNA-seq data. Briefings in Bioinformatics. 25(6). 2 indexed citations
2.
Wei, Feifei, Taku Kouro, Yuko Nakamura, et al.. (2024). Enhancing Mass spectrometry-based tumor immunopeptide identification: machine learning filter leveraging HLA binding affinity, aliphatic index and retention time deviation. Computational and Structural Biotechnology Journal. 23. 859–869. 6 indexed citations
3.
Mukasa, Akitake, Masashi Nomura, Genta Nagae, et al.. (2024). Region‐specific DNA hydroxymethylation along the malignant progression of IDH‐mutant gliomas. Cancer Science. 115(5). 1706–1717. 1 indexed citations
4.
Ueda, Hiroki, Bhaskar Dasgupta, & Boyi Yu. (2023). RNA Modification Detection Using Nanopore Direct RNA Sequencing and nanoDoc2. Methods in molecular biology. 2632. 299–319. 4 indexed citations
5.
Hayashi, Gosuke, Hiroki Ueda, Satoshi Ota, et al.. (2021). Base-resolution analysis of 5-hydroxymethylcytidine by selective oxidation and reverse transcription arrest. Organic & Biomolecular Chemistry. 19(29). 6478–6486. 2 indexed citations
6.
Ikeda, Mio, Yasuhiro Koh, Jun Oyanagi, et al.. (2021). High-purity Isolation for Genotyping Rare Cancer Cells from Blood Using a Microfluidic Chip Cell Sorter. Anticancer Research. 42(1). 407–417. 3 indexed citations
7.
Ishiguro, Soh, Hideto Mori, Mamoru Tanaka, et al.. (2020). Publisher Correction: Base editors for simultaneous introduction of C-to-T and A-to-G mutations. Nature Biotechnology. 38(7). 901–901. 2 indexed citations
8.
Ishiguro, Soh, Hideto Mori, Mamoru Tanaka, et al.. (2020). Base editors for simultaneous introduction of C-to-T and A-to-G mutations. Nature Biotechnology. 38(7). 865–869. 151 indexed citations
9.
Midorikawa, Yutaka, Shogo Yamamoto, Kenji Tatsuno, et al.. (2020). Accumulation of Molecular Aberrations Distinctive to Hepatocellular Carcinoma Progression. Cancer Research. 80(18). 3810–3819. 22 indexed citations
10.
Sakurai, Masayuki, et al.. (2020). Discovering A-to-I RNA Editing Through Chemical Methodology “ICE-seq”. Methods in molecular biology. 2181. 113–148. 3 indexed citations
11.
Okada, Shunpei, et al.. (2018). Transcriptome-wide identification of A-to-I RNA editing sites using ICE-seq. Methods. 156. 66–78. 11 indexed citations
12.
Suzuki, Tsutomu, Hiroki Ueda, Shunpei Okada, & Masayuki Sakurai. (2015). Transcriptome-wide identification of adenosine-to-inosine editing using the ICE-seq method. Nature Protocols. 10(5). 715–732. 70 indexed citations
13.
Sakurai, Masayuki, Hiroki Ueda, Takanori Yano, et al.. (2014). A biochemical landscape of A-to-I RNA editing in the human brain transcriptome. Genome Research. 24(3). 522–534. 115 indexed citations
14.
Johnson, Brett, Tali Mazor, Michael J. Barnes, et al.. (2014). GE-15 * CLONAL EVOLUTION AND INTRATUMORAL HETEROGENEITY OF LOW-GRADE GLIOMA GENOMES. Neuro-Oncology. 16(suppl 5). v99–v99. 1 indexed citations
15.
Sakurai, Masayuki, Takanori Yano, Hitomi Kawabata, Hiroki Ueda, & Tsutomu Suzuki. (2010). Inosine cyanoethylation identifies A-to-I RNA editing sites in the human transcriptome. Nature Chemical Biology. 6(10). 733–740. 161 indexed citations
16.
Sumida, Motoyuki & Hiroki Ueda. (2007). Dietary Sucrose Suppresses Midgut Sucrase Activity in Germfree, Fifth Instar Larvae of the Silkworm, Bombyx mori. Journal of insect biotechnology and sericology. 76(1). 31–37. 9 indexed citations
17.
Sakaguchi, Yuriko, et al.. (2007). The 3′ termini of mouse Piwi-interacting RNAs are 2′-O-methylated. Nature Structural & Molecular Biology. 14(4). 349–350. 181 indexed citations
18.
Ueda, Hiroki, Shohei Shinozaki, Takashi Kitajima, et al.. (2007). Hepatocyte Growth Factor Fusion Protein Having Collagen-Binding Activity (CBD-HGF) Accelerates Re-endothelialization and Intimal Hyperplasia in Balloon-injured Rat Carotid Artery. Journal of Atherosclerosis and Thrombosis. 14(4). 185–191. 14 indexed citations
19.
Nakamura, Tatsuo, Yasuhiko Shimizu, Yukinobu Takimoto, et al.. (1999). Intrathoracic esophageal replacement in the dog with the use of an artificial esophagus composed of a collagen sponge with a double-layered silicone tube. Journal of Thoracic and Cardiovascular Surgery. 118(2). 276–286. 75 indexed citations
20.

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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