Ivo Ugrina
About
In The Last Decade
Ivo Ugrina
25 papers receiving 579 citations
Peers
Comparison fields: 5 of 92
- Molecular Biology 308
- Immunology 155
- Radiology, Nuclear Medicine and Imaging 121
- Pharmaceutical Science 82
- Genetics 77
Countries citing papers authored by Ivo Ugrina
This map shows the geographic impact of Ivo Ugrina'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 Ivo Ugrina with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ivo Ugrina more than expected).
Fields of papers citing papers by Ivo Ugrina
This network shows the impact of papers produced by Ivo Ugrina. 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 Ivo Ugrina. The network helps show where Ivo Ugrina may publish in the future.
Co-authorship network of co-authors of Ivo Ugrina
This figure shows the co-authorship network connecting the top 25 collaborators of Ivo Ugrina. A scholar is included among the top collaborators of Ivo Ugrina 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 Ivo Ugrina. Ivo Ugrina is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 27 | |
| 2 | 15 | |
| 3 | 18 | |
| 4 | 12 | |
| 5 | 34 | |
| 6 | 12 | |
| 7 | 15 | |
| 8 | Choosing proper normalization is essential for discovery of sparse glycan biomarkers | 2 |
| 9 | 32 | |
| 10 | 61 | |
| 11 | 22 | |
| 12 | 4 | |
| 13 | 25 | |
| 14 | 36 | |
| 15 | 4 | |
| 16 | 69 | |
| 17 | 53 | |
| 18 | 51 | |
| 19 | 11 | |
| 20 | 10 |
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.