Tatsuya Tamaoki
- Molecular Biology top 1%
- Oncology top 5%
- Organic Chemistry top 2%
- Cell Biology top 2%
- Pharmacology top 1%
- Co-authors
- Makoto MorimotoISAMI TAKAHASHIFusao TomitaHirofumi NakanoYuzuru KatoEiji KobayashiShiro AkinagaMasami Okabe
- Topics
- Microbial Natural Products and Biosynthesis (17 papers)Bioactive Compounds and Antitumor Agents (11 papers)Cancer therapeutics and mechanisms (10 papers)
- Partner nations
- JapanSingaporeUnited States
In The Last Decade
Tatsuya Tamaoki
66 papers receiving 6.4k citations
Hit Papers
Peers
Comparison fields: 5 of 127
- Molecular Biology 4.3k
- Oncology 926
- Organic Chemistry 749
- Cell Biology 719
- Pharmacology 714
Countries citing papers authored by Tatsuya Tamaoki
This map shows the geographic impact of Tatsuya Tamaoki'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 Tatsuya Tamaoki with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tatsuya Tamaoki more than expected).
Fields of papers citing papers by Tatsuya Tamaoki
This network shows the impact of papers produced by Tatsuya Tamaoki. 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 Tatsuya Tamaoki. The network helps show where Tatsuya Tamaoki may publish in the future.
Co-authorship network of co-authors of Tatsuya Tamaoki
This figure shows the co-authorship network connecting the top 25 collaborators of Tatsuya Tamaoki. A scholar is included among the top collaborators of Tatsuya Tamaoki 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 Tatsuya Tamaoki. Tatsuya Tamaoki is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 24 | |
| 2 | 13 | |
| 3 | 11 | |
| 4 | 63 | |
| 5 | Decrease in susceptibility toward induction of apoptosis and alteration in G1 checkpoint function as determinants of resistance of human lung cancer cells against the antisignaling drug UCN-01 (7-Hydroxystaurosporine). | 30 |
| 6 | 31 | |
| 7 | 21 | |
| 8 | 28 | |
| 9 | 36 | |
| 10 | 12 | |
| 11 | 27 | |
| 12 | 6 | |
| 13 | 48 | |
| 14 | 69 | |
| 15 | 45 | |
| 16 | 31 | |
| 17 | Antitumor activity of UCN-01, a selective inhibitor of protein kinase C, in murine and human tumor models. | 167 |
| 18 | 88 | |
| 19 | 38 | |
| 20 | 182 |
About Tatsuya Tamaoki
Tatsuya Tamaoki is a scholar working on Toxicology, Biotechnology and Pharmacology, having authored 66 papers that have together received 6.6k indexed citations. Recurring topics across this work include Microbial Natural Products and Biosynthesis (17 papers), Bioactive Compounds and Antitumor Agents (11 papers) and Cancer therapeutics and mechanisms (10 papers). The work is most often cited by research in Toxicology (301 citations), Molecular Biology (4.3k citations) and Cell Biology (719 citations). Tatsuya Tamaoki has collaborated with scholars based in Japan, Singapore and United States. Frequent co-authors include Makoto Morimoto, ISAMI TAKAHASHI, Fusao Tomita, Hirofumi Nakano, Yuzuru Kato, Eiji Kobayashi, Hirofumi Nakano, Shiro Akinaga, Eiji Kobayashi and Masami Okabe. Their work appears in journals such as Blood, Nature Biotechnology and Analytical Biochemistry.
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.