Daiki Omata

1.2k total citations
46 papers, 909 citations indexed

About

Daiki Omata is a scholar working on Biomedical Engineering, Materials Chemistry and Molecular Biology. According to data from OpenAlex, Daiki Omata has authored 46 papers receiving a total of 909 indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Biomedical Engineering, 15 papers in Materials Chemistry and 14 papers in Molecular Biology. Recurrent topics in Daiki Omata's work include Ultrasound and Hyperthermia Applications (32 papers), Photoacoustic and Ultrasonic Imaging (20 papers) and Ultrasound and Cavitation Phenomena (15 papers). Daiki Omata is often cited by papers focused on Ultrasound and Hyperthermia Applications (32 papers), Photoacoustic and Ultrasonic Imaging (20 papers) and Ultrasound and Cavitation Phenomena (15 papers). Daiki Omata collaborates with scholars based in Japan, New Zealand and United States. Daiki Omata's co-authors include Ryo Suzuki, Kazuo Maruyama, Yoichi Negishi, Yukihiko Aramaki, Johan Unga, Motoyoshi Nomizu, Yoko Endo‐Takahashi, Yoko Endo, Tomoko Takizawa and Nobuhito Hamano and has published in prestigious journals such as ACS Nano, Biomaterials and Advanced Drug Delivery Reviews.

In The Last Decade

Daiki Omata

45 papers receiving 898 citations

Peers

Daiki Omata

BIOMA

IMMUN

Yoko Endo‐Takahashi Japan

Xiuli Chen China

Adam Yuh Lin United States

Julia Zhou United States

Huapan Fang China

Matthew T. Basel United States

Raisa Y. Kiseleva United States

Kyung Eun Lee South Korea

Yong Serk Park South Korea

Yoko Endo‐Takahashi Japan

Daiki Omata

538 ×1.0

488 ×1.4

259 ×1.2

BIOMA

233 ×1.1

75 ×0.8

IMMUN

Citations per year, relative to Daiki Omata Daiki Omata (= 1×) peers Yoko Endo‐Takahashi

Countries citing papers authored by Daiki Omata

Since Specialization

Citations

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

Fields of papers citing papers by Daiki Omata

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daiki Omata

This figure shows the co-authorship network connecting the top 25 collaborators of Daiki Omata. A scholar is included among the top collaborators of Daiki Omata 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 Omata. Daiki Omata is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Miyamoto, Yoshitaka, et al.. (2025). Burst wave conditions for vascular endothelial cells retained on channel wall using lipid bubbles and acoustic interference modulation. Japanese Journal of Applied Physics. 64(5). 05SP19–05SP19.

Kawai, Atsushi, Masahiro Noda, Daiki Omata, et al.. (2024). Lipid Nanoparticle with 1,2-Di-O-octadecenyl-3-trimethylammonium-propane as a Component Lipid Confers Potent Responses of Th1 Cells and Antibody against Vaccine Antigen. ACS Nano. 18(26). 16589–16609. 7 indexed citations

Yoshida, Naoya, et al.. (2024). Investigation of damage in vascular endothelial cells caused by lipid bubbles under ultrasound irradiation to verify the protective effect on cells. Japanese Journal of Applied Physics. 63(4). 04SP25–04SP25. 3 indexed citations

Omata, Daiki, et al.. (2024). Effect of Anti-PEG Antibody on Immune Response of mRNA-Loaded Lipid Nanoparticles. Molecular Pharmaceutics. 21(11). 5672–5680. 9 indexed citations

Miyamoto, Yoshitaka, et al.. (2023). Viability variation of T-cells under ultrasound exposure according to adhesion condition with bubbles. Journal of Medical Ultrasonics. 50(2). 121–129. 3 indexed citations

Omata, Daiki, et al.. (2022). Feasibility Study of Novel Nanoparticles Derived from Glycyrrhizae Radix as Vaccine Adjuvant for Cancer Immunotherapy. Immunotherapy. 14(18). 1443–1455. 2 indexed citations

Miyamoto, Yoshitaka, et al.. (2022). Validation of damage on vascular endothelial cells under ultrasound exposure according to adhered situation of bubbles. Japanese Journal of Applied Physics. 61(SG). SG1066–SG1066. 7 indexed citations

Miyamoto, Yoshitaka, et al.. (2022). Experimental study of ultrasound retention of bubble-surrounded cells under various conditions of acoustic field and flow velocity. Japanese Journal of Applied Physics. 61(SG). SG1071–SG1071. 6 indexed citations

Omata, Daiki, et al.. (2022). Ultrasound and microbubble-mediated drug delivery and immunotherapy. Journal of Medical Ultrasonics. 12 indexed citations

10.

Omata, Daiki, et al.. (2020). Effect of lipid shell composition in DSPG-based microbubbles on blood flow imaging with ultrasonography. International Journal of Pharmaceutics. 590. 119886–119886. 4 indexed citations

11.

Omata, Daiki, Takashi Azuma, Shu Takagi, et al.. (2020). Characterization of Brain-Targeted Drug Delivery Enhanced by a Combination of Lipid-Based Microbubbles and Non-Focused Ultrasound. Journal of Pharmaceutical Sciences. 109(9). 2827–2835. 12 indexed citations

12.

Masuda, Kohji, et al.. (2020). Evaluation of damage on vascular endothelial cells under exposure of burst wave with presence of lipid bubbles. 1–2. 3 indexed citations

13.

Oda, Yusuke, Ryo Suzuki, Hideyo Takahashi, et al.. (2015). Development of fluorous lipid-based nanobubbles for efficiently containing perfluoropropane. International Journal of Pharmaceutics. 487(1-2). 64–71. 19 indexed citations

14.

Omata, Daiki, Yoichi Negishi, Ryo Suzuki, et al.. (2014). Nonviral Gene Delivery Systems by the Combination of Bubble Liposomes and Ultrasound. Advances in genetics. 89. 25–48. 13 indexed citations

15.

Suzuki, Ryo, Yusuke Oda, Daiki Omata, et al.. (2013). Novel Strategies for Ultrasound Diagnostics and Therapeutics by Micro/Nanobubbles. 29(2). 37–46. 1 indexed citations

16.

Negishi, Yoichi, Nobuhito Hamano, Yusuke Oda, et al.. (2012). AG73-modified Bubble liposomes for targeted ultrasound imaging of tumor neovasculature. Biomaterials. 34(2). 501–507. 52 indexed citations

17.

Hamano, Nobuhito, Yoichi Negishi, Daiki Omata, et al.. (2012). Bubble Liposomes and Ultrasound Enhance the Antitumor Effects of AG73 Liposomes Encapsulating Antitumor Agents. Molecular Pharmaceutics. 10(2). 774–779. 19 indexed citations

18.

Omata, Daiki, Yoichi Negishi, Yoko Endo‐Takahashi, et al.. (2012). Enhanced gene delivery using Bubble liposomes and ultrasound for folate-PEG liposomes. Journal of drug targeting. 20(4). 355–363. 15 indexed citations

19.

Negishi, Yoichi, et al.. (2011). Effects of doxorubicin-encapsulating AG73 peptide-modified liposomes on tumor selectivity and cytotoxicity. PubMed. 1(1). 68–75. 12 indexed citations

20.

Iijima, Hiroshi, Yoichi Negishi, Daiki Omata, Motoyoshi Nomizu, & Yukihiko Aramaki. (2010). Cancer cell specific gene delivery by laminin-derived peptide AG73-labeled liposomes. Bioorganic & Medicinal Chemistry Letters. 20(15). 4712–4714. 6 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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