Kazuko Hattori
About
In The Last Decade
Kazuko Hattori
4 papers receiving 2.3k citations
Hit Papers
Peers
Comparison fields: 5 of 103
- Immunology 1.4k
- Molecular Biology 1.2k
- Epidemiology 345
- Oncology 239
- Hematology 192
Countries citing papers authored by Kazuko Hattori
This map shows the geographic impact of Kazuko Hattori'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 Kazuko Hattori with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kazuko Hattori more than expected).
Fields of papers citing papers by Kazuko Hattori
This network shows the impact of papers produced by Kazuko Hattori. 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 Kazuko Hattori. The network helps show where Kazuko Hattori may publish in the future.
Co-authorship network of co-authors of Kazuko Hattori
This figure shows the co-authorship network connecting the top 25 collaborators of Kazuko Hattori. A scholar is included among the top collaborators of Kazuko Hattori 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 Kazuko Hattori. Kazuko Hattori is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 61 | |
| 3 | 58 | |
| 4 | Cloning of a new cytokine that induces IFN-γ production by T cells breakdown → | 2244 |
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.