Francesca Fanelli
- Molecular Biology top 1%
- Cellular and Molecular Neuroscience top 0.5%
- Computational Theory and Mathematics top 0.5%
- Reproductive Medicine top 1%
- Radiology, Nuclear Medicine and Imaging top 2%
- Co-authors
- Pier G. De BenedettiDeborah L. SegaloffSusanna CotecchiaMario AscoliAngelo FellineAlexander ScheerMichele SeeberFrancesco Raimondi
- Topics
- Receptor Mechanisms and Signaling (101 papers)Neuropeptides and Animal Physiology (35 papers)Computational Drug Discovery Methods (28 papers)
- Journals
- Chemical ReviewsProceedings of the National Academy of SciencesJournal of the American Chemical Society
- Partner nations
- ItalyUnited StatesSwitzerland
In The Last Decade
Francesca Fanelli
163 papers receiving 6.0k citations
Hit Papers
Peers
Comparison fields: 5 of 133
- Molecular Biology 4.6k
- Cellular and Molecular Neuroscience 2.5k
- Computational Theory and Mathematics 722
- Reproductive Medicine 620
- Radiology, Nuclear Medicine and Imaging 530
Countries citing papers authored by Francesca Fanelli
This map shows the geographic impact of Francesca Fanelli'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 Francesca Fanelli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Francesca Fanelli more than expected).
Fields of papers citing papers by Francesca Fanelli
This network shows the impact of papers produced by Francesca Fanelli. 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 Francesca Fanelli. The network helps show where Francesca Fanelli may publish in the future.
Co-authorship network of co-authors of Francesca Fanelli
This figure shows the co-authorship network connecting the top 25 collaborators of Francesca Fanelli. A scholar is included among the top collaborators of Francesca Fanelli 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 Francesca Fanelli. Francesca Fanelli is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 3 | |
| 4 | 6 | |
| 5 | 8 | |
| 6 | 42 | |
| 7 | 1 | |
| 8 | 40 | |
| 9 | 98 | |
| 10 | 39 | |
| 11 | 6 | |
| 12 | 20 | |
| 13 | 56 | |
| 14 | 26 | |
| 15 | 12 | |
| 16 | 71 | |
| 17 | 1 | |
| 18 | 37 | |
| 19 | 71 | |
| 20 | ET A とET B 受容体およびC末端エンドセリンヘキサペプチドきっ抗薬の三次元模型に対する構造-親和性/選択性関係の定量解析 | 1 |
About Francesca Fanelli
Francesca Fanelli is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Computational Theory and Mathematics, having authored 164 papers that have together received 6.1k indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (101 papers), Neuropeptides and Animal Physiology (35 papers) and Computational Drug Discovery Methods (28 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (2.5k citations), Physiology (392 citations) and Reproductive Medicine (620 citations). Francesca Fanelli has collaborated with scholars based in Italy, United States and Switzerland. Frequent co-authors include Pier G. De Benedetti, Deborah L. Segaloff, Susanna Cotecchia, Mario Ascoli, Angelo Felline, Alexander Scheer, Michele Seeber, Francesco Raimondi, Tommaso Costa and Maria Cristina Menziani. Their work appears in journals such as Chemical Reviews, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.
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.