Mai Nitta
About
In The Last Decade
Mai Nitta
5 papers receiving 663 citations
Hit Papers
Peers
Comparison fields: 5 of 60
- Molecular Biology 334
- Genetics 318
- Cancer Research 290
- Oncology 168
- Pulmonary and Respiratory Medicine 97
Countries citing papers authored by Mai Nitta
This map shows the geographic impact of Mai Nitta'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 Mai Nitta with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mai Nitta more than expected).
Fields of papers citing papers by Mai Nitta
This network shows the impact of papers produced by Mai Nitta. 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 Mai Nitta. The network helps show where Mai Nitta may publish in the future.
Co-authorship network of co-authors of Mai Nitta
This figure shows the co-authorship network connecting the top 25 collaborators of Mai Nitta. A scholar is included among the top collaborators of Mai Nitta 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 Mai Nitta. Mai Nitta 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 | 31 | |
| 3 | Mosaic Amplification of Multiple Receptor Tyrosine Kinase Genes in Glioblastoma breakdown → | 498 |
| 4 | 91 | |
| 5 | 47 |
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.