Takuya Niimoto
About
In The Last Decade
Takuya Niimoto
14 papers receiving 808 citations
Peers
Comparison fields: 5 of 68
- Cancer Research 484
- Molecular Biology 434
- Rheumatology 299
- Surgery 140
- Immunology 98
Countries citing papers authored by Takuya Niimoto
This map shows the geographic impact of Takuya Niimoto'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 Niimoto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Takuya Niimoto more than expected).
Fields of papers citing papers by Takuya Niimoto
This network shows the impact of papers produced by Takuya Niimoto. 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 Niimoto. The network helps show where Takuya Niimoto may publish in the future.
Co-authorship network of co-authors of Takuya Niimoto
This figure shows the co-authorship network connecting the top 25 collaborators of Takuya Niimoto. A scholar is included among the top collaborators of Takuya Niimoto 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 Niimoto. Takuya Niimoto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | 20 | |
| 3 | 8 | |
| 4 | 55 | |
| 5 | 36 | |
| 6 | 11 | |
| 7 | 57 | |
| 8 | 10 | |
| 9 | 256 | |
| 10 | 24 | |
| 11 | 198 | |
| 12 | 124 | |
| 13 | 12 | |
| 14 | 2 |
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.