Hiroshi Yamada
- Molecular Biology top 5%
- Epidemiology top 5%
- Computational Theory and Mathematics top 1%
- Infectious Diseases top 5%
- Pharmacology top 1%
- Co-authors
- Tetsuro UrushidaniAtsushi OnoYasuo OhnoNoriyuki NakatsuYoshinobu IgarashiIkuo HoriiHiroshi KidoTakeki Uehara
- Topics
- 3D IC and TSV technologies (18 papers)Influenza Virus Research Studies (16 papers)Computational Drug Discovery Methods (15 papers)
- Journals
- Journal of the American Chemical SocietyNucleic Acids ResearchThe Journal of Chemical Physics
- Partner nations
- JapanUnited StatesSouth Korea
In The Last Decade
Hiroshi Yamada
125 papers receiving 3.1k citations
Peers
Comparison fields: 5 of 154
- Molecular Biology 1.4k
- Epidemiology 714
- Computational Theory and Mathematics 516
- Infectious Diseases 400
- Pharmacology 382
Countries citing papers authored by Hiroshi Yamada
This map shows the geographic impact of Hiroshi Yamada'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 Hiroshi Yamada with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hiroshi Yamada more than expected).
Fields of papers citing papers by Hiroshi Yamada
This network shows the impact of papers produced by Hiroshi Yamada. 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 Hiroshi Yamada. The network helps show where Hiroshi Yamada may publish in the future.
Co-authorship network of co-authors of Hiroshi Yamada
This figure shows the co-authorship network connecting the top 25 collaborators of Hiroshi Yamada. A scholar is included among the top collaborators of Hiroshi Yamada 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 Hiroshi Yamada. Hiroshi Yamada is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 12 | |
| 4 | 5 | |
| 5 | 11 | |
| 6 | 3 | |
| 7 | TXPO: A Toxic Process Ontology for Better Understanding of Drug-Induced Liver Injury. | 2 |
| 8 | 10 | |
| 9 | 40 | |
| 10 | 13 | |
| 11 | 3 | |
| 12 | 12 | |
| 13 | 12 | |
| 14 | 69 | |
| 15 | 15 | |
| 16 | 8 | |
| 17 | 4 | |
| 18 | Effects of Bi content on mechanical properties and bump interconnection reliability of Sn-Ag solder alloys | 10 |
| 19 | GaAs MMICs using BCB thin film layers for automotive radar and wireless communication application | 4 |
| 20 | The Adaptive Transversal Equalizer for 90MBPS 64-QAM Radio Relay System. | 1 |
About Hiroshi Yamada
Hiroshi Yamada is a scholar working on Pharmacology, Infectious Diseases and Computational Theory and Mathematics, having authored 136 papers that have together received 3.2k indexed citations. Recurring topics across this work include 3D IC and TSV technologies (18 papers), Influenza Virus Research Studies (16 papers) and Computational Drug Discovery Methods (15 papers). The work is most often cited by research in Pharmacology (382 citations), Computational Theory and Mathematics (516 citations) and Infectious Diseases (400 citations). Hiroshi Yamada has collaborated with scholars based in Japan, United States and South Korea. Frequent co-authors include Tetsuro Urushidani, Atsushi Ono, Yasuo Ohno, Noriyuki Nakatsu, Yoshinobu Igarashi, Ikuo Horii, Hiroshi Kido, Takeki Uehara, Toshinori Yamamoto and Rie Kikkawa. Their work appears in journals such as Journal of the American Chemical Society, Nucleic Acids Research and The Journal of Chemical Physics.
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.