Takuya Matsuo
- Endocrine and Autonomic Systems top 0.5%
- Plant Science top 5%
- Molecular Biology
- Cellular and Molecular Neuroscience top 5%
- Physiology top 5%
- Co-authors
- Shun YamaguchiHitoshi OkamuraAki EmiShigeru MitsuiMasaki KobayashiKazuhiro YagitaMasahiro IshiuraKiyoshi Onai
- Topics
- Light effects on plants (14 papers)Circadian rhythm and melatonin (10 papers)Algal biology and biofuel production (9 papers)
In The Last Decade
Takuya Matsuo
24 papers receiving 2.0k citations
Hit Papers
Peers
Comparison fields: 5 of 108
- Endocrine and Autonomic Systems 1.3k
- Plant Science 645
- Molecular Biology 600
- Cellular and Molecular Neuroscience 533
- Physiology 445
Countries citing papers authored by Takuya Matsuo
This map shows the geographic impact of Takuya Matsuo'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 Takuya Matsuo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Takuya Matsuo more than expected).
Fields of papers citing papers by Takuya Matsuo
This network shows the impact of papers produced by Takuya Matsuo. 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 Takuya Matsuo. The network helps show where Takuya Matsuo may publish in the future.
Co-authorship network of co-authors of Takuya Matsuo
This figure shows the co-authorship network connecting the top 25 collaborators of Takuya Matsuo. A scholar is included among the top collaborators of Takuya Matsuo 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 Takuya Matsuo. Takuya Matsuo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | 9 | |
| 7 | 43 | |
| 8 | 11 | |
| 9 | 6 | |
| 10 | 9 | |
| 11 | 10 | |
| 12 | 9 | |
| 13 | 37 | |
| 14 | 30 | |
| 15 | 98 | |
| 16 | Synchronization of Cellular Clocks in the Suprachiasmatic Nucleusbreakdown → | 722 |
| 17 | Control Mechanism of the Circadian Clock for Timing of Cell Division in Vivobreakdown → | 894 |
| 18 | 4 | |
| 19 | Studies on the genetics of heading period in rice. II. Genetic analysis of X-ray-induced early mutant strains. | 1 |
| 20 | Studies on the genetics of heading period in rice. I. The characteristics of some heading-period mutants induced by irradiation. | 1 |
About Takuya Matsuo
Takuya Matsuo is a scholar working on Endocrine and Autonomic Systems, Renewable Energy, Sustainability and the Environment and Plant Science, having authored 27 papers that have together received 2.0k indexed citations. Recurring topics across this work include Light effects on plants (14 papers), Circadian rhythm and melatonin (10 papers) and Algal biology and biofuel production (9 papers). The work is most often cited by research in Endocrine and Autonomic Systems (1.3k citations), Aging (223 citations) and Cellular and Molecular Neuroscience (533 citations). Takuya Matsuo has collaborated with scholars based in Japan, China and Germany. Frequent co-authors include Shun Yamaguchi, Hitoshi Okamura, Aki Emi, Shigeru Mitsui, Masaki Kobayashi, Kazuhiro Yagita, Masahiro Ishiura, Kiyoshi Onai, Kazuhisa Okamoto and Jun Minagawa. Their work appears in journals such as Science, Proceedings of the National Academy of Sciences and Nature Communications.
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.