Takuya Kobayashi
- Molecular Biology top 2%
- Pharmacology top 0.5%
- Cellular and Molecular Neuroscience top 1%
- Physiology top 2%
- Genetics top 2%
- Co-authors
- Shuh NarumiyaYukihiko SugimotoSo IwataFumitaka UshikubiMitsunori ShiroishiTakami Yurugi-KobayashiTatsuro ShimamuraTatsunori Murata
- Topics
- Receptor Mechanisms and Signaling (33 papers)Inflammatory mediators and NSAID effects (15 papers)Neuropeptides and Animal Physiology (11 papers)
- Partner nations
- JapanUnited KingdomUnited States
In The Last Decade
Takuya Kobayashi
81 papers receiving 6.2k citations
Hit Papers
Peers
Comparison fields: 5 of 139
- Molecular Biology 3.4k
- Pharmacology 1.4k
- Cellular and Molecular Neuroscience 1.2k
- Physiology 796
- Genetics 727
Countries citing papers authored by Takuya Kobayashi
This map shows the geographic impact of Takuya Kobayashi'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 Takuya Kobayashi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Takuya Kobayashi more than expected).
Fields of papers citing papers by Takuya Kobayashi
This network shows the impact of papers produced by Takuya Kobayashi. 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 Takuya Kobayashi. The network helps show where Takuya Kobayashi may publish in the future.
Co-authorship network of co-authors of Takuya Kobayashi
This figure shows the co-authorship network connecting the top 25 collaborators of Takuya Kobayashi. A scholar is included among the top collaborators of Takuya Kobayashi 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 Takuya Kobayashi. Takuya Kobayashi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 14 | |
| 2 | 25 | |
| 3 | 4 | |
| 4 | 38 | |
| 5 | 2 | |
| 6 | 54 | |
| 7 | 53 | |
| 8 | 25 | |
| 9 | 6 | |
| 10 | 19 | |
| 11 | 39 | |
| 12 | Structure of the human M2 muscarinic acetylcholine receptor bound to an antagonistbreakdown → | 634 |
| 13 | 19 | |
| 14 | 6 | |
| 15 | Evaluation of Reputations in CGM based on Identification of Reviewer's Activity Area | 0 |
| 16 | 257 | |
| 17 | 371 | |
| 18 | 377 | |
| 19 | 273 | |
| 20 | 455 |
About Takuya Kobayashi
Takuya Kobayashi is a scholar working on Cellular and Molecular Neuroscience, Orthopedics and Sports Medicine and Pharmacology, having authored 83 papers that have together received 6.3k indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (33 papers), Inflammatory mediators and NSAID effects (15 papers) and Neuropeptides and Animal Physiology (11 papers). The work is most often cited by research in Pharmacology (1.4k citations), Biochemistry (528 citations) and Cellular and Molecular Neuroscience (1.2k citations). Takuya Kobayashi has collaborated with scholars based in Japan, United Kingdom and United States. Frequent co-authors include Shuh Narumiya, Yukihiko Sugimoto, So Iwata, Fumitaka Ushikubi, Mitsunori Shiroishi, Takami Yurugi-Kobayashi, Tatsuro Shimamura, Tatsunori Murata, Atsushi Ichikawa and Masakazu Hirata. Their work appears in journals such as Nature, Science and Proceedings of the National Academy of Sciences.
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.