Go Sekimoto
About
In The Last Decade
Go Sekimoto
12 papers receiving 862 citations
Peers
Comparison fields: 5 of 75
- Molecular Biology 607
- Oncology 386
- Hepatology 258
- Epidemiology 175
- Pathology and Forensic Medicine 135
Countries citing papers authored by Go Sekimoto
This map shows the geographic impact of Go Sekimoto'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 Go Sekimoto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Go Sekimoto more than expected).
Fields of papers citing papers by Go Sekimoto
This network shows the impact of papers produced by Go Sekimoto. 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 Go Sekimoto. The network helps show where Go Sekimoto may publish in the future.
Co-authorship network of co-authors of Go Sekimoto
This figure shows the co-authorship network connecting the top 25 collaborators of Go Sekimoto. A scholar is included among the top collaborators of Go Sekimoto 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 Go Sekimoto. Go Sekimoto 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 | 1 | |
| 3 | 5 | |
| 4 | 16 | |
| 5 | 113 | |
| 6 | 141 | |
| 7 | 2 | |
| 8 | 3 | |
| 9 | 120 | |
| 10 | 245 | |
| 11 | 81 | |
| 12 | 156 |
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.