Satoru Kuhara
- Molecular Biology top 1%
- Plant Science top 2%
- Genetics top 2%
- Infectious Diseases top 2%
- Biomedical Engineering top 5%
- Co-authors
- Satoru MiyanoTatsuya AkutsuKosuke TashiroHideki HirakawaYoshiyuki SakakiAtsushi YamashitaTetsuya HayashiMasahira Hattori
- Topics
- Gene expression and cancer classification (32 papers)Bioinformatics and Genomic Networks (28 papers)Gene Regulatory Network Analysis (22 papers)
- Partner nations
- JapanUnited StatesUnited Kingdom
In The Last Decade
Satoru Kuhara
198 papers receiving 7.9k citations
Hit Papers
Peers
Comparison fields: 5 of 179
- Molecular Biology 5.4k
- Plant Science 928
- Genetics 905
- Infectious Diseases 877
- Biomedical Engineering 544
Countries citing papers authored by Satoru Kuhara
This map shows the geographic impact of Satoru Kuhara'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 Satoru Kuhara with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Satoru Kuhara more than expected).
Fields of papers citing papers by Satoru Kuhara
This network shows the impact of papers produced by Satoru Kuhara. 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 Satoru Kuhara. The network helps show where Satoru Kuhara may publish in the future.
Co-authorship network of co-authors of Satoru Kuhara
This figure shows the co-authorship network connecting the top 25 collaborators of Satoru Kuhara. A scholar is included among the top collaborators of Satoru Kuhara 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 Satoru Kuhara. Satoru Kuhara is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 7 | |
| 3 | 27 | |
| 4 | 38 | |
| 5 | 116 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 5 | |
| 9 | 16 | |
| 10 | 2 | |
| 11 | 2 | |
| 12 | 462 | |
| 13 | 67 | |
| 14 | 5 | |
| 15 | Development of a Deductive Database System for Computing Closures of Similarity Relationships among Protein Structures | 2 |
| 16 | Data Classification Component in a Deductive Database System and Its Application to Protein Structural Analysis | 2 |
| 17 | 7 | |
| 18 | 1 | |
| 19 | 3 | |
| 20 | 0 |
About Satoru Kuhara
Satoru Kuhara is a scholar working on Molecular Biology, Endocrinology and Biotechnology, having authored 203 papers that have together received 8.1k indexed citations. Recurring topics across this work include Gene expression and cancer classification (32 papers), Bioinformatics and Genomic Networks (28 papers) and Gene Regulatory Network Analysis (22 papers). The work is most often cited by research in Endocrinology (468 citations), Molecular Biology (5.4k citations) and Infectious Diseases (877 citations). Satoru Kuhara has collaborated with scholars based in Japan, United States and United Kingdom. Frequent co-authors include Satoru Miyano, Tatsuya Akutsu, Kosuke Tashiro, Hideki Hirakawa, Yoshiyuki Sakaki, Atsushi Yamashita, Tetsuya Hayashi, Masahira Hattori, Kousuke Tashiro and Shigeru Muta. Their work appears in journals such as Nature, Proceedings of the National Academy of Sciences and Nucleic Acids Research.
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.