Antonella Cavalli
- Molecular Biology
- Cellular and Molecular Neuroscience top 5%
- Physiology top 10%
- Endocrinology, Diabetes and Metabolism
- Surgery
- Co-authors
- Li‐Na WeiHorace H. LohSusanna CotecchiaGraeme MilliganKirk M. DrueyEdith HümmlerAndrea SchmidtMartin C. Michel
- Topics
- Receptor Mechanisms and Signaling (7 papers)Neuropeptides and Animal Physiology (5 papers)COVID-19 Clinical Research Studies (4 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of Biological ChemistryThe Journal of Clinical Endocrinology & Metabolism
- Partner nations
- ItalyUnited KingdomUnited States
In The Last Decade
Antonella Cavalli
19 papers receiving 979 citations
Peers
Comparison fields: 5 of 85
- Molecular Biology 662
- Cellular and Molecular Neuroscience 492
- Physiology 192
- Endocrinology, Diabetes and Metabolism 96
- Surgery 66
Countries citing papers authored by Antonella Cavalli
This map shows the geographic impact of Antonella Cavalli'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 Antonella Cavalli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Antonella Cavalli more than expected).
Fields of papers citing papers by Antonella Cavalli
This network shows the impact of papers produced by Antonella Cavalli. 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 Antonella Cavalli. The network helps show where Antonella Cavalli may publish in the future.
Co-authorship network of co-authors of Antonella Cavalli
This figure shows the co-authorship network connecting the top 25 collaborators of Antonella Cavalli. A scholar is included among the top collaborators of Antonella Cavalli 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 Antonella Cavalli. Antonella Cavalli is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 19 | |
| 2 | 8 | |
| 3 | 18 | |
| 4 | 23 | |
| 5 | 19 | |
| 6 | 90 | |
| 7 | 16 | |
| 8 | 27 | |
| 9 | 12 | |
| 10 | 12 | |
| 11 | 4 | |
| 12 | 27 | |
| 13 | 32 | |
| 14 | 58 | |
| 15 | 1 | |
| 16 | 290 | |
| 17 | 251 | |
| 18 | 71 | |
| 19 | 30 |
About Antonella Cavalli
Antonella Cavalli is a scholar working on Internal Medicine, Cellular and Molecular Neuroscience and Radiation, having authored 19 papers that have together received 1.0k indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (7 papers), Neuropeptides and Animal Physiology (5 papers) and COVID-19 Clinical Research Studies (4 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (492 citations), Molecular Biology (662 citations) and Internal Medicine (32 citations). Antonella Cavalli has collaborated with scholars based in Italy, United Kingdom and United States. Frequent co-authors include Li‐Na Wei, Horace H. Loh, Susanna Cotecchia, Graeme Milligan, Kirk M. Druey, Edith Hümmler, Andrea Schmidt, Martin C. Michel, Friedrich Beermann and Marina Mostardini. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and The Journal of Clinical Endocrinology & Metabolism.
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.