Reiji Teramoto
- Molecular Biology
- Computational Theory and Mathematics top 5%
- Radiology, Nuclear Medicine and Imaging
- Cancer Research
- Physiology
- Co-authors
- Hiroaki FukunishiTōru KimuraMasaharu KanaokaMikio AokiManabu WadaKenji YoshidaHiroyuki TsunodaTeruyuki Ueda
- Topics
- Computational Drug Discovery Methods (7 papers)Bioinformatics and Genomic Networks (4 papers)Gene expression and cancer classification (4 papers)
- Cited by
- Computational Theory and MathematicsMolecular BiologyRadiology, Nuclear Medicine and Imaging
- Journals
- Proceedings of the National Academy of SciencesScientific ReportsBiochemical and Biophysical Research Communications
- Partner nations
- JapanUnited StatesSweden
In The Last Decade
Reiji Teramoto
21 papers receiving 453 citations
Peers
Comparison fields: 5 of 94
- Molecular Biology 327
- Computational Theory and Mathematics 128
- Radiology, Nuclear Medicine and Imaging 75
- Cancer Research 39
- Physiology 37
Countries citing papers authored by Reiji Teramoto
This map shows the geographic impact of Reiji Teramoto'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 Reiji Teramoto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Reiji Teramoto more than expected).
Fields of papers citing papers by Reiji Teramoto
This network shows the impact of papers produced by Reiji Teramoto. 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 Reiji Teramoto. The network helps show where Reiji Teramoto may publish in the future.
Co-authorship network of co-authors of Reiji Teramoto
This figure shows the co-authorship network connecting the top 25 collaborators of Reiji Teramoto. A scholar is included among the top collaborators of Reiji Teramoto 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 Reiji Teramoto. Reiji Teramoto 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 | 87 | |
| 3 | 5 | |
| 4 | 1 | |
| 5 | 10 | |
| 6 | 10 | |
| 7 | 42 | |
| 8 | 7 | |
| 9 | 7 | |
| 10 | 8 | |
| 11 | 8 | |
| 12 | 30 | |
| 13 | 26 | |
| 14 | 66 | |
| 15 | 9 | |
| 16 | 54 | |
| 17 | 50 | |
| 18 | 1 | |
| 19 | A method for clustering gene expression data based on graph structure. | 7 |
| 20 | 2 |
About Reiji Teramoto
Reiji Teramoto is a scholar working on Computational Theory and Mathematics, Molecular Biology and Pharmacology, having authored 21 papers that have together received 470 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (7 papers), Bioinformatics and Genomic Networks (4 papers) and Gene expression and cancer classification (4 papers). The work is most often cited by research in Computational Theory and Mathematics (128 citations), Molecular Biology (327 citations) and Radiology, Nuclear Medicine and Imaging (75 citations). Reiji Teramoto has collaborated with scholars based in Japan, United States and Sweden. Frequent co-authors include Hiroaki Fukunishi, Tōru Kimura, Masaharu Kanaoka, Mikio Aoki, Manabu Wada, Kenji Yoshida, Hiroyuki Tsunoda, Teruyuki Ueda, Shuichi Kaneko and Kenichi Kamijo. Their work appears in journals such as Proceedings of the National Academy of Sciences, Scientific Reports and Biochemical and Biophysical Research 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.