Eriko Shikata
About
In The Last Decade
Eriko Shikata
5 papers receiving 520 citations
Peers
Comparison fields: 5 of 74
- Molecular Biology 235
- Endocrinology, Diabetes and Metabolism 190
- Oncology 160
- Pharmacology 146
- Cell Biology 84
Countries citing papers authored by Eriko Shikata
This map shows the geographic impact of Eriko Shikata'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 Eriko Shikata with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eriko Shikata more than expected).
Fields of papers citing papers by Eriko Shikata
This network shows the impact of papers produced by Eriko Shikata. 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 Eriko Shikata. The network helps show where Eriko Shikata may publish in the future.
Co-authorship network of co-authors of Eriko Shikata
This figure shows the co-authorship network connecting the top 25 collaborators of Eriko Shikata. A scholar is included among the top collaborators of Eriko Shikata 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 Eriko Shikata. Eriko Shikata is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 111 | |
| 2 | 159 | |
| 3 | 127 | |
| 4 | 129 | |
| 5 | [A case of variant Gerstmann-Sträussler-Scheinker disease with the mutation of codon P105L]. | 9 |
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.