Yoji Sato

6.0k total citations
123 papers, 4.2k citations indexed

About

Yoji Sato is a scholar working on Molecular Biology, Physiology and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Yoji Sato has authored 123 papers receiving a total of 4.2k indexed citations (citations by other indexed papers that have themselves been cited), including 89 papers in Molecular Biology, 28 papers in Physiology and 24 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Yoji Sato's work include Pluripotent Stem Cells Research (39 papers), CRISPR and Genetic Engineering (26 papers) and Biomedical Ethics and Regulation (23 papers). Yoji Sato is often cited by papers focused on Pluripotent Stem Cells Research (39 papers), CRISPR and Genetic Engineering (26 papers) and Biomedical Ethics and Regulation (23 papers). Yoji Sato collaborates with scholars based in Japan, United States and United Kingdom. Yoji Sato's co-authors include Motohiro Nishida, Satoshi Yasuda, Yasuo Mori, Ryuji Inoue, Hitoshi Kurose, Takuya Kuroda, Taku Nagao, Kazuhide Inoue, Naoya Onohara and Evangelia G. Kranias and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Yoji Sato

116 papers receiving 4.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yoji Sato Japan 36 2.6k 965 751 623 573 123 4.2k
Karen E. Porter United Kingdom 44 2.5k 1.0× 1.9k 2.0× 767 1.0× 647 1.0× 1.3k 2.3× 131 5.6k
Attila Braun Germany 37 1.7k 0.7× 454 0.5× 1.0k 1.4× 322 0.5× 255 0.4× 75 4.4k
Xiang Luo United States 33 2.2k 0.9× 1.1k 1.2× 243 0.3× 502 0.8× 600 1.0× 47 4.0k
Xuefeng Xia China 35 2.8k 1.1× 477 0.5× 170 0.2× 861 1.4× 490 0.9× 110 4.9k
Grigori Y. Rychkov Australia 35 2.2k 0.9× 453 0.5× 1.1k 1.4× 577 0.9× 347 0.6× 86 4.0k
Lan Mao United States 39 2.5k 1.0× 2.1k 2.2× 141 0.2× 687 1.1× 409 0.7× 84 5.1k
Chou-Long Huang United States 46 4.1k 1.6× 848 0.9× 592 0.8× 427 0.7× 485 0.8× 84 6.3k
Anne‐Marie Lompré France 41 3.8k 1.5× 3.5k 3.6× 274 0.4× 544 0.9× 483 0.8× 92 6.1k
Gervaise Loirand France 48 3.6k 1.4× 1.6k 1.7× 180 0.2× 1.4k 2.2× 891 1.6× 133 6.5k
Shigeki Miyamoto United States 40 3.9k 1.5× 1.3k 1.4× 100 0.1× 709 1.1× 476 0.8× 72 5.8k

Countries citing papers authored by Yoji Sato

Since Specialization
Citations

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

Fields of papers citing papers by Yoji Sato

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yoji Sato

This figure shows the co-authorship network connecting the top 25 collaborators of Yoji Sato. A scholar is included among the top collaborators of Yoji Sato 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 Yoji Sato. Yoji Sato 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
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Terai, Shuji, Ayuko Hoshino, Masahiro Kino‐oka, et al.. (2025). Guidance on the clinical application of extracellular vesicles. Regenerative Therapy. 29. 43–50. 3 indexed citations
3.
Terai, Shuji, Sachiko Ezoe, Yumi Matsuzaki, et al.. (2025). Recommendations for the safe implementation of intravenous administration of mesenchymal stromal cells. Regenerative Therapy. 29. 171–176. 2 indexed citations
4.
Yamamoto, Eiichi, et al.. (2024). Physicochemical profiling of nanomedicines using centrifugal field flow fractionation. International Journal of Pharmaceutics. 663. 124571–124571. 2 indexed citations
5.
Bando, Kiyoko, Shinji Kusakawa, Hideki Adachi, et al.. (2024). Protocol improvement and multisite validation of a digital soft agar colony formation assay for tumorigenic transformed cells intermingled in cell therapy products. Cytotherapy. 26(7). 769–777. 4 indexed citations
6.
Yoshida, Hiroyuki, et al.. (2024). Comparison of in vitro screening methods for evaluating the effects of pharmaceutical excipients on membrane permeability. International Journal of Pharmaceutics. 665. 124727–124727. 1 indexed citations
7.
Yoshida, Hiroyuki, et al.. (2023). Effects of Apex Size on Dissolution Profiles in the USP II Paddle Apparatus. AAPS PharmSciTech. 25(1). 9–9. 1 indexed citations
8.
Yasuda, Satoshi, et al.. (2023). Country-specific regulation and international standardization of cell-based therapeutic products derived from pluripotent stem cells. Stem Cell Reports. 18(8). 1573–1591. 19 indexed citations
9.
Matsuzaka, Yasunari, Shinji Kusakawa, Yoshihiro Uesawa, Yoji Sato, & Mitsutoshi Satoh. (2021). Deep Learning-Based In Vitro Detection Method for Cellular Impurities in Human Cell-Processed Therapeutic Products. Applied Sciences. 11(20). 9755–9755. 1 indexed citations
10.
Kono, Ken, et al.. (2020). A highly sensitive method for the detection of recombinant PERV-A/C env RNA using next generation sequencing technologies. Scientific Reports. 10(1). 21935–21935. 7 indexed citations
11.
Ouhara, Kazuhisa, Mikihito Kajiya, Katsuhiro Takeda, et al.. (2018). The induced RNA-binding protein, HuR, targets 3′-UTR region of IL-6 mRNA and enhances its stabilization in periodontitis. Clinical & Experimental Immunology. 192(3). 325–336. 35 indexed citations
12.
Lysaght, Tamra, Megan Munsie, James Hoi Po Hui, et al.. (2018). A roundtable on responsible innovation with autologous stem cells in Australia, Japan and Singapore. Cytotherapy. 20(9). 1103–1109. 8 indexed citations
13.
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Kuroda, Takuya, Satoshi Yasuda, Satoko Matsuyama, et al.. (2015). Highly sensitive droplet digital PCR method for detection of residual undifferentiated cells in cardiomyocytes derived from human pluripotent stem cells. Regenerative Therapy. 2. 17–23. 39 indexed citations
15.
Kono, Ken, Nozomi Takada, Satoshi Yasuda, et al.. (2014). Characterization of the cell growth analysis for detection of immortal cellular impurities in human mesenchymal stem cells. Biologicals. 43(2). 146–149. 18 indexed citations
16.
Jin, Meihua, Utako Yokoyama, Yoji Sato, et al.. (2011). DNA microarray profiling identified a new role of growth hormone in vascular remodeling of rat ductus arteriosus. The Journal of Physiological Sciences. 61(3). 167–179. 30 indexed citations
17.
Nishida, Motohiro, K. Watanabe, Yoji Sato, et al.. (2010). Phosphorylation of TRPC6 Channels at Thr69 Is Required for Anti-hypertrophic Effects of Phosphodiesterase 5 Inhibition. Journal of Biological Chemistry. 285(17). 13244–13253. 83 indexed citations
18.
Kitano, Etsuko, Yoji Sato, Tadao K. Kobayashi, et al.. (2008). Investigation of Cynomolgus Monkey Complement. Transplantation Proceedings. 40(2). 607–608. 1 indexed citations
19.
Fujino, Tomofumi, Yoji Sato, Mizuho Une, et al.. (2003). In vitro farnesoid X receptor ligand sensor assay using surface plasmon resonance and based on ligand-induced coactivator association. The Journal of Steroid Biochemistry and Molecular Biology. 87(4-5). 247–252. 25 indexed citations
20.
Tanaka, Hirotoshi, Yuichi Makino, Takumi Miura, et al.. (1996). Ligand-independent activation of the glucocorticoid receptor by ursodeoxycholic acid. Repression of IFN-γ-induced MHC class II gene expression via a glucocorticoid receptor-dependent pathway. The Journal of Immunology. 156(4). 1601–1608. 91 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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