Yujiro Kidani
About
In The Last Decade
Yujiro Kidani
7 papers receiving 494 citations
Hit Papers
Peers
Comparison fields: 5 of 55
- Immunology 381
- Molecular Biology 117
- Oncology 65
- Genetics 49
- Developmental Neuroscience 29
Countries citing papers authored by Yujiro Kidani
This map shows the geographic impact of Yujiro Kidani'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 Yujiro Kidani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yujiro Kidani more than expected).
Fields of papers citing papers by Yujiro Kidani
This network shows the impact of papers produced by Yujiro Kidani. 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 Yujiro Kidani. The network helps show where Yujiro Kidani may publish in the future.
Co-authorship network of co-authors of Yujiro Kidani
This figure shows the co-authorship network connecting the top 25 collaborators of Yujiro Kidani. A scholar is included among the top collaborators of Yujiro Kidani 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 Yujiro Kidani. Yujiro Kidani is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 30 | |
| 3 | 1 | |
| 4 | 151 | |
| 5 | Guidance of regulatory T cell development by Satb1-dependent super-enhancer establishment breakdown → | 262 |
| 6 | 33 | |
| 7 | 16 |
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.