S. Takeda
- Molecular Biology
- Global and Planetary Change top 10%
- Cellular and Molecular Neuroscience top 10%
- Physiology
- Cell Biology
- Co-authors
- Katsunori KobayashiTakeshi NodaTakehiro TakahashiNobutaka HirokawaYasuyuki KosakaSumio TeradaYosuke TakeiAkihiro Harada
- Topics
- Conservation, Biodiversity, and Resource Management (15 papers)Southeast Asian Sociopolitical Studies (7 papers)Vietnamese History and Culture Studies (6 papers)
In The Last Decade
S. Takeda
38 papers receiving 783 citations
Peers
Comparison fields: 5 of 133
- Molecular Biology 198
- Global and Planetary Change 144
- Cellular and Molecular Neuroscience 136
- Physiology 107
- Cell Biology 99
Countries citing papers authored by S. Takeda
This map shows the geographic impact of S. Takeda'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 S. Takeda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S. Takeda more than expected).
Fields of papers citing papers by S. Takeda
This network shows the impact of papers produced by S. Takeda. 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 S. Takeda. The network helps show where S. Takeda may publish in the future.
Co-authorship network of co-authors of S. Takeda
This figure shows the co-authorship network connecting the top 25 collaborators of S. Takeda. A scholar is included among the top collaborators of S. Takeda 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 S. Takeda. S. Takeda is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 7 | |
| 2 | 20 | |
| 3 | 2 | |
| 4 | 2 | |
| 5 | 4 | |
| 6 | 22 | |
| 7 | 13 | |
| 8 | Leptin and bone signaling | 1 |
| 9 | Effects of selective logging on the regeneration of two commercial tree species in the Kabaung Reserved Forest, Bago Mountains, Myanmar. | 8 |
| 10 | 13 | |
| 11 | 3 | |
| 12 | 0 | |
| 13 | 4 | |
| 14 | 265 | |
| 15 | 4 | |
| 16 | Negamycin can restore dystrophin in mdx skeletal muscle | 6 |
| 17 | The Profitability of Eucalyptus Farm Forest in Northeast Thailand | 2 |
| 18 | [Introduction of rod-deleted dystrophin cDNA, delta DysM3, into mdx skeletal muscle using adenovirus vector]. | 10 |
| 19 | 148 | |
| 20 | Dynamics of Upland Utilization and Forest Land Management : A Case Study in Yasothon Province, Northeast Thailand | 9 |
About S. Takeda
S. Takeda is a scholar working on Global and Planetary Change, Soil Science and General Agricultural and Biological Sciences, having authored 40 papers that have together received 812 indexed citations. Recurring topics across this work include Conservation, Biodiversity, and Resource Management (15 papers), Southeast Asian Sociopolitical Studies (7 papers) and Vietnamese History and Culture Studies (6 papers). The work is most often cited by research in Endocrine and Autonomic Systems (86 citations), Orthopedics and Sports Medicine (81 citations) and Forestry (31 citations). S. Takeda has collaborated with scholars based in Japan, Laos and Bulgaria. Frequent co-authors include Katsunori Kobayashi, Takeshi Noda, Takehiro Takahashi, Nobutaka Hirokawa, Yasuyuki Kosaka, Sumio Terada, Yosuke Takei, Akihiro Harada, Yoshihiro Ogawa and Charles Vinson. Their work appears in journals such as Proceedings of the National Academy of Sciences, The Journal of Cell Biology and Bone.
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.