Paolo Laveder
About
In The Last Decade
Paolo Laveder
12 papers receiving 541 citations
Peers
Comparison fields: 5 of 79
- Molecular Biology 414
- Cardiology and Cardiovascular Medicine 133
- Physiology 98
- Genetics 93
- Cellular and Molecular Neuroscience 83
Countries citing papers authored by Paolo Laveder
This map shows the geographic impact of Paolo Laveder'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 Paolo Laveder with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paolo Laveder more than expected).
Fields of papers citing papers by Paolo Laveder
This network shows the impact of papers produced by Paolo Laveder. 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 Paolo Laveder. The network helps show where Paolo Laveder may publish in the future.
Co-authorship network of co-authors of Paolo Laveder
This figure shows the co-authorship network connecting the top 25 collaborators of Paolo Laveder. A scholar is included among the top collaborators of Paolo Laveder 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 Paolo Laveder. Paolo Laveder is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 19 | |
| 3 | 80 | |
| 4 | 17 | |
| 5 | 63 | |
| 6 | 82 | |
| 7 | 55 | |
| 8 | 68 | |
| 9 | 2 | |
| 10 | 141 | |
| 11 | 24 | |
| 12 | 3 |
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.