Hideaki Umeyama
- Molecular Biology top 5%
- Atomic and Molecular Physics, and Optics top 5%
- Organic Chemistry top 5%
- Physical and Theoretical Chemistry top 1%
- Spectroscopy top 2%
- Co-authors
- Keiji MorokumaSetsuko NakagawaMitsuo IwadateKoji OgataMayuko Takeda‐ShitakaY‐h. TaguchiKenji AkahaneKenshu Kamiya
- Topics
- Protein Structure and Dynamics (37 papers)Computational Drug Discovery Methods (20 papers)Enzyme Structure and Function (18 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of the American Chemical SocietyJournal of Biological Chemistry
- Partner nations
- JapanUnited StatesUnited Kingdom
In The Last Decade
Hideaki Umeyama
159 papers receiving 3.0k citations
Hit Papers
Peers
Comparison fields: 5 of 130
- Molecular Biology 1.4k
- Atomic and Molecular Physics, and Optics 650
- Organic Chemistry 509
- Physical and Theoretical Chemistry 505
- Spectroscopy 505
Countries citing papers authored by Hideaki Umeyama
This map shows the geographic impact of Hideaki Umeyama'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 Hideaki Umeyama with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hideaki Umeyama more than expected).
Fields of papers citing papers by Hideaki Umeyama
This network shows the impact of papers produced by Hideaki Umeyama. 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 Hideaki Umeyama. The network helps show where Hideaki Umeyama may publish in the future.
Co-authorship network of co-authors of Hideaki Umeyama
This figure shows the co-authorship network connecting the top 25 collaborators of Hideaki Umeyama. A scholar is included among the top collaborators of Hideaki Umeyama 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 Hideaki Umeyama. Hideaki Umeyama is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 11 | |
| 3 | 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 |
| 4 | 21 | |
| 5 | 28 | |
| 6 | 6 | |
| 7 | 10 | |
| 8 | 5 | |
| 9 | 6 | |
| 10 | 76 | |
| 11 | 7 | |
| 12 | 12 | |
| 13 | 20 | |
| 14 | 2 | |
| 15 | 12 | |
| 16 | 19 | |
| 17 | 6 | |
| 18 | 16 | |
| 19 | 25 | |
| 20 | 10 |
About Hideaki Umeyama
Hideaki Umeyama is a scholar working on Spectroscopy, Physical and Theoretical Chemistry and Hematology, having authored 160 papers that have together received 3.1k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (37 papers), Computational Drug Discovery Methods (20 papers) and Enzyme Structure and Function (18 papers). The work is most often cited by research in Physical and Theoretical Chemistry (505 citations), Computational Mathematics (25 citations) and Spectroscopy (505 citations). Hideaki Umeyama has collaborated with scholars based in Japan, United States and United Kingdom. Frequent co-authors include Keiji Morokuma, Setsuko Nakagawa, Mitsuo Iwadate, Koji Ogata, Mayuko Takeda‐Shitaka, Y‐h. Taguchi, Kenji Akahane, Kenshu Kamiya, S. YONEDA and Tetsuhiro Kubota. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society 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.