Daichi Sato

24 papers receiving 340 citations

Peers

Daichi Sato
Comparison fields: 5 of 80
  • Aging 15
  • Cell Biology 115
  • Cellular and Molecular Neuroscience 79
  • Developmental Neuroscience 9
  • Radiology, Nuclear Medicine and Imaging 46
Replace Kalina T. Haas with:
Kalina T. Haas France
Sílvia Llonch Germany
Margaret R. Starostik United States
Xiaobo Bai United States
Jonathan R. Bowen United States
Tetsuo Ichii Japan
Dhevahi Niranjan United Kingdom
Maurício Rocha-Martins Germany
Yotam Menuchin-Lasowski Israel
Julien Maruotti United States
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Citations per field
00.5×6.7×
Kalina T. Haas · 1×
Citations per year

Countries citing papers authored by Daichi Sato

Since Specialization
Citations

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

Fields of papers citing papers by Daichi Sato

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Daichi Sato, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daichi Sato Line = papers co-authored together Daichi Sato links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008159
2 201331
3 201622
4 202022
5 202018
6 201913
7 202211
8 20229
9 20109
10
The karyotype analysis in Zingi-berales with special reference to the protokaryotype and stable karyotype.
19608
11 20248
12 20227
13 20136
14 20225
15 20135
16
Law of karyotype evolution with special reference to the protokaryotype.
19623
17 20042
18 20212
19 20212
20 20172

About Daichi Sato

Daichi Sato is a scholar working on Biomedical Engineering, Radiology, Nuclear Medicine and Imaging, Molecular Biology, Electrical and Electronic Engineering and Surgery, having authored 30 papers that have together received 348 indexed citations. Recurring topics across this work include Advanced X-ray and CT Imaging (13 papers), Medical Imaging Techniques and Applications (11 papers), Radiation Dose and Imaging (10 papers), Radiation Detection and Scintillator Technologies (2 papers), Epigenetics and DNA Methylation (2 papers), Nuclear Physics and Applications (2 papers), Reproductive Biology and Fertility (2 papers) and Chemical and Physical Properties in Aqueous Solutions (1 paper). The work is most often cited by research in Aging (15 citations), Cell Biology (115 citations), Cellular and Molecular Neuroscience (79 citations), Developmental Neuroscience (9 citations) and Radiology, Nuclear Medicine and Imaging (46 citations). Daichi Sato has collaborated with scholars based in Japan, United States and Thailand. Frequent co-authors include Tadashi Uemura, Daisuke Satoh, Melissa M. Rolls, Motoki Saito, Fuyuki Ishikawa, Hiroyuki Ohkura, Taiichi Tsuyama, Takehito Kuwayama, Tetsuhiko Isobe and Y. Monji. Their work appears in journals such as Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment, Journal of Instrumentation, Langmuir, European Journal of Medical Genetics and Theriogenology.

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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