Shinya Koyama
- Molecular Biology top 10%
- Cell Biology top 5%
- Oncology
- Pathology and Forensic Medicine top 10%
- Surgery
- Co-authors
- Akira KikuchiShosei KishidaDaniel K. PodolskySatoshi IkedaHideki YamamotoMichiko KishidaIkuo SakamotoShintaro Nakashima
- Topics
- Protein Kinase Regulation and GTPase Signaling (8 papers)Biochemical Acid Research Studies (5 papers)Metabolism and Genetic Disorders (4 papers)
- Journals
- Journal of Biological ChemistryJournal of Clinical InvestigationThe Journal of Cell Biology
- Partner nations
- JapanUnited StatesCanada
In The Last Decade
Shinya Koyama
42 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 89
- Molecular Biology 1.1k
- Cell Biology 252
- Oncology 197
- Pathology and Forensic Medicine 117
- Surgery 107
Countries citing papers authored by Shinya Koyama
This map shows the geographic impact of Shinya Koyama'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 Koyama with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shinya Koyama more than expected).
Fields of papers citing papers by Shinya Koyama
This network shows the impact of papers produced by Shinya Koyama. 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 Koyama. The network helps show where Shinya Koyama may publish in the future.
Co-authorship network of co-authors of Shinya Koyama
This figure shows the co-authorship network connecting the top 25 collaborators of Shinya Koyama. A scholar is included among the top collaborators of Shinya Koyama 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 Koyama. Shinya Koyama is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 49 | |
| 4 | 18 | |
| 5 | 418 | |
| 6 | 59 | |
| 7 | 8 | |
| 8 | 35 | |
| 9 | 14 | |
| 10 | 81 | |
| 11 | 24 | |
| 12 | 6 | |
| 13 | 17 | |
| 14 | 18 | |
| 15 | 5 | |
| 16 | 2 | |
| 17 | 197 | |
| 18 | 3 | |
| 19 | [Large tumors of the chest wall and its reconstruction with Marlex mesh--report of 5 cases]. | 0 |
| 20 | Content of thiamin phosphate esters in mammalian tissues--an extremely high concentration of thiamin triphosphate in pig skeletal muscle. | 25 |
About Shinya Koyama
Shinya Koyama is a scholar working on Biochemistry, Neurology and Clinical Biochemistry, having authored 43 papers that have together received 1.5k indexed citations. Recurring topics across this work include Protein Kinase Regulation and GTPase Signaling (8 papers), Biochemical Acid Research Studies (5 papers) and Metabolism and Genetic Disorders (4 papers). The work is most often cited by research in Molecular Biology (1.1k citations), Cell Biology (252 citations) and Biochemistry (72 citations). Shinya Koyama has collaborated with scholars based in Japan, United States and Canada. Frequent co-authors include Akira Kikuchi, Shosei Kishida, Daniel K. Podolsky, Satoshi Ikeda, Hideki Yamamoto, Michiko Kishida, Ikuo Sakamoto, Shintaro Nakashima, Kenji Matsubara and Takaaki Uochi. Their work appears in journals such as Journal of Biological Chemistry, Journal of Clinical Investigation and The Journal of Cell Biology.
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.