Y‐h. Taguchi
- Molecular Biology top 5%
- Cancer Research top 5%
- Computational Mechanics top 5%
- Condensed Matter Physics top 5%
- Materials Chemistry
- Co-authors
- Y. OonoPaul C. ZamecnikJohn GoodchildPrem S. SarinYoshiki MurakamiTurki TurkiHidetoshi NishimoriM. Michael Gromiha
- Topics
- Machine Learning in Bioinformatics (28 papers)RNA modifications and cancer (23 papers)Tensor decomposition and applications (20 papers)
- Journals
- Proceedings of the National Academy of SciencesPhysical Review LettersJournal of Biological Chemistry
- Partner nations
- JapanSaudi ArabiaIndia
In The Last Decade
Y‐h. Taguchi
147 papers receiving 2.7k citations
Peers
Comparison fields: 5 of 176
- Molecular Biology 1.4k
- Cancer Research 416
- Computational Mechanics 330
- Condensed Matter Physics 221
- Materials Chemistry 217
Countries citing papers authored by Y‐h. Taguchi
This map shows the geographic impact of Y‐h. Taguchi'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 Y‐h. Taguchi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Y‐h. Taguchi more than expected).
Fields of papers citing papers by Y‐h. Taguchi
This network shows the impact of papers produced by Y‐h. Taguchi. 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 Y‐h. Taguchi. The network helps show where Y‐h. Taguchi may publish in the future.
Co-authorship network of co-authors of Y‐h. Taguchi
This figure shows the co-authorship network connecting the top 25 collaborators of Y‐h. Taguchi. A scholar is included among the top collaborators of Y‐h. Taguchi 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 Y‐h. Taguchi. Y‐h. Taguchi 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 | 1 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 3 | |
| 6 | 4 | |
| 7 | 4 | |
| 8 | 3 | |
| 9 | 15 | |
| 10 | 3 | |
| 11 | 27 | |
| 12 | 16 | |
| 13 | 27 | |
| 14 | Discrimination of symbiotic/parasitic bacterial type III secretion system effector protein using principal component analysis (ニューロコンピューティング) | 1 |
| 15 | 21 | |
| 16 | 57 | |
| 17 | 185 | |
| 18 | 3 | |
| 19 | 8 | |
| 20 | 32 |
About Y‐h. Taguchi
Y‐h. Taguchi is a scholar working on Computational Mathematics, Cancer Research and Molecular Biology, having authored 156 papers that have together received 2.8k indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (28 papers), RNA modifications and cancer (23 papers) and Tensor decomposition and applications (20 papers). The work is most often cited by research in Computational Mathematics (152 citations), Cancer Research (416 citations) and Virology (94 citations). Y‐h. Taguchi has collaborated with scholars based in Japan, Saudi Arabia and India. Frequent co-authors include Y. Oono, Paul C. Zamecnik, John Goodchild, Prem S. Sarin, Yoshiki Murakami, Turki Turki, Hidetoshi Nishimori, M. Michael Gromiha, Hideaki Umeyama and Mitsuo Iwadate. Their work appears in journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and Journal of Biological Chemistry.
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.