Shinya Nakamura
- Molecular Biology top 10%
- Plant Science top 5%
- Organic Chemistry top 10%
- Endocrinology, Diabetes and Metabolism top 10%
- Cardiology and Cardiovascular Medicine
- Co-authors
- Tetsuya KimuraKenzo NakamuraTsuyoshi NakagawaSumie IshiguroKatsunori TanakaTakamasa SuzukiYasuo NiwaRyo Tabata
- Topics
- Protein Kinase Regulation and GTPase Signaling (9 papers)Computational Drug Discovery Methods (8 papers)Natural Antidiabetic Agents Studies (7 papers)
- Partner nations
- JapanChinaUnited States
In The Last Decade
Shinya Nakamura
63 papers receiving 1.6k citations
Hit Papers
Peers
Comparison fields: 5 of 123
- Molecular Biology 913
- Plant Science 704
- Organic Chemistry 170
- Endocrinology, Diabetes and Metabolism 134
- Cardiology and Cardiovascular Medicine 127
Countries citing papers authored by Shinya Nakamura
This map shows the geographic impact of Shinya Nakamura'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 Shinya Nakamura with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shinya Nakamura more than expected).
Fields of papers citing papers by Shinya Nakamura
This network shows the impact of papers produced by Shinya Nakamura. 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 Shinya Nakamura. The network helps show where Shinya Nakamura may publish in the future.
Co-authorship network of co-authors of Shinya Nakamura
This figure shows the co-authorship network connecting the top 25 collaborators of Shinya Nakamura. A scholar is included among the top collaborators of Shinya Nakamura 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 Shinya Nakamura. Shinya Nakamura 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 | 1 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | 4 | |
| 6 | 3 | |
| 7 | 1 | |
| 8 | 15 | |
| 9 | 4 | |
| 10 | 2 | |
| 11 | 12 | |
| 12 | 23 | |
| 13 | 19 | |
| 14 | Membranous nephropathy occurred in a patient with Turner's syndrome during rhGH treatment | 1 |
| 15 | 20 | |
| 16 | 30 | |
| 17 | 3 | |
| 18 | Improved Gateway Binary Vectors: High-Performance Vectors for Creation of Fusion Constructs in Transgenic Analysis of Plantsbreakdown → | 743 |
| 19 | 4 | |
| 20 | 11 |
About Shinya Nakamura
Shinya Nakamura is a scholar working on Nephrology, Biotechnology and Endocrinology, Diabetes and Metabolism, having authored 67 papers that have together received 1.7k indexed citations. Recurring topics across this work include Protein Kinase Regulation and GTPase Signaling (9 papers), Computational Drug Discovery Methods (8 papers) and Natural Antidiabetic Agents Studies (7 papers). The work is most often cited by research in Plant Science (704 citations), Molecular Biology (913 citations) and Nephrology (85 citations). Shinya Nakamura has collaborated with scholars based in Japan, China and United States. Frequent co-authors include Tetsuya Kimura, Kenzo Nakamura, Tsuyoshi Nakagawa, Sumie Ishiguro, Katsunori Tanaka, Takamasa Suzuki, Yasuo Niwa, Ryo Tabata, Satoko Murata and Yuichiro Watanabe. Their work appears in journals such as Angewandte Chemie International Edition, Circulation and Neurology.
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.