Gabriele Flekna
About
In The Last Decade
Gabriele Flekna
7 papers receiving 400 citations
Peers
Comparison fields: 5 of 61
- Food Science 212
- Molecular Biology 171
- Biotechnology 127
- Biomedical Engineering 89
- Endocrinology 79
Countries citing papers authored by Gabriele Flekna
This map shows the geographic impact of Gabriele Flekna'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 Gabriele Flekna with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gabriele Flekna more than expected).
Fields of papers citing papers by Gabriele Flekna
This network shows the impact of papers produced by Gabriele Flekna. 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 Gabriele Flekna. The network helps show where Gabriele Flekna may publish in the future.
Co-authorship network of co-authors of Gabriele Flekna
This figure shows the co-authorship network connecting the top 25 collaborators of Gabriele Flekna. A scholar is included among the top collaborators of Gabriele Flekna 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 Gabriele Flekna. Gabriele Flekna is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 58 | |
| 2 | 17 | |
| 3 | 47 | |
| 4 | 105 | |
| 5 | 36 | |
| 6 | 120 | |
| 7 | 26 |
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.