Koushi Hidaka
- Molecular Biology top 10%
- Computational Theory and Mathematics top 1%
- Organic Chemistry top 5%
- Physiology top 10%
- Materials Chemistry
- Co-authors
- Yoshiaki KisoTooru KimuraYoshio HayashiAlan K. SoperToshio YamaguchiErnesto FreireY. HamadaHiroshi Sugiyama
- Topics
- Computational Drug Discovery Methods (22 papers)HIV/AIDS drug development and treatment (14 papers)Chemical Synthesis and Analysis (12 papers)
- Journals
- Proceedings of the National Academy of SciencesNucleic Acids ResearchAngewandte Chemie International Edition
- Partner nations
- JapanUnited StatesCanada
In The Last Decade
Koushi Hidaka
73 papers receiving 1.8k citations
Peers
Comparison fields: 5 of 117
- Molecular Biology 913
- Computational Theory and Mathematics 502
- Organic Chemistry 333
- Physiology 295
- Materials Chemistry 220
Countries citing papers authored by Koushi Hidaka
This map shows the geographic impact of Koushi Hidaka'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 Koushi Hidaka with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Koushi Hidaka more than expected).
Fields of papers citing papers by Koushi Hidaka
This network shows the impact of papers produced by Koushi Hidaka. 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 Koushi Hidaka. The network helps show where Koushi Hidaka may publish in the future.
Co-authorship network of co-authors of Koushi Hidaka
This figure shows the co-authorship network connecting the top 25 collaborators of Koushi Hidaka. A scholar is included among the top collaborators of Koushi Hidaka 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 Koushi Hidaka. Koushi Hidaka is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 44 | |
| 2 | 10 | |
| 3 | 15 | |
| 4 | 7 | |
| 5 | 15 | |
| 6 | 15 | |
| 7 | 28 | |
| 8 | 41 | |
| 9 | 24 | |
| 10 | 14 | |
| 11 | 35 | |
| 12 | 40 | |
| 13 | 52 | |
| 14 | Evaluation of Peptidomimetic Inhibitors against Malarial Protease Plasmepsin | 1 |
| 15 | 70 | |
| 16 | 13 | |
| 17 | 30 | |
| 18 | 52 | |
| 19 | Substrate Transition-State Analogue Inhibitors of Plasmepsin II as Antimalarial Drugs | 1 |
| 20 | 22 |
About Koushi Hidaka
Koushi Hidaka is a scholar working on Virology, Computational Theory and Mathematics and Infectious Diseases, having authored 74 papers that have together received 1.8k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (22 papers), HIV/AIDS drug development and treatment (14 papers) and Chemical Synthesis and Analysis (12 papers). The work is most often cited by research in Computational Theory and Mathematics (502 citations), Virology (73 citations) and Aging (24 citations). Koushi Hidaka has collaborated with scholars based in Japan, United States and Canada. Frequent co-authors include Yoshiaki Kiso, Tooru Kimura, Yoshio Hayashi, Alan K. Soper, Toshio Yamaguchi, Ernesto Freire, Y. Hamada, Hiroshi Sugiyama, Masayuki Endo and Jeffrey‐Tri Nguyen. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Angewandte Chemie International Edition.
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.