Andrea Cavalli
- Molecular Biology top 0.5%
- Computational Theory and Mathematics top 0.02%
- Pharmacology top 0.05%
- Organic Chemistry top 0.2%
- Physiology top 1%
- Co-authors
- Maurizio RecanatiniMaría Laura BolognesiMatteo MasettiGiovanni BottegoniMarco De VivoCarlo MelchiorreVincenza AndrisanoMichela Rosini
- Topics
- Computational Drug Discovery Methods (85 papers)Protein Structure and Dynamics (55 papers)Cholinesterase and Neurodegenerative Diseases (55 papers)
- Journals
- Chemical ReviewsProceedings of the National Academy of SciencesJournal of the American Chemical Society
- Partner nations
- ItalySwitzerlandUnited States
In The Last Decade
Andrea Cavalli
301 papers receiving 14.7k citations
Hit Papers
Peers
Comparison fields: 5 of 184
- Molecular Biology 7.0k
- Computational Theory and Mathematics 4.6k
- Pharmacology 4.6k
- Organic Chemistry 3.9k
- Physiology 1.7k
Countries citing papers authored by Andrea Cavalli
This map shows the geographic impact of Andrea 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 Andrea Cavalli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrea Cavalli more than expected).
Fields of papers citing papers by Andrea Cavalli
This network shows the impact of papers produced by Andrea 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 Andrea Cavalli. The network helps show where Andrea Cavalli may publish in the future.
Co-authorship network of co-authors of Andrea Cavalli
This figure shows the co-authorship network connecting the top 25 collaborators of Andrea Cavalli. A scholar is included among the top collaborators of Andrea 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 Andrea Cavalli. Andrea 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 | 1 | |
| 2 | 6 | |
| 3 | 0 | |
| 4 | 2 | |
| 5 | 3 | |
| 6 | 10 | |
| 7 | 7 | |
| 8 | 11 | |
| 9 | 7 | |
| 10 | 6 | |
| 11 | 35 | |
| 12 | 26 | |
| 13 | 12 | |
| 14 | 50 | |
| 15 | 4 | |
| 16 | 14 | |
| 17 | 46 | |
| 18 | 23 | |
| 19 | 25 | |
| 20 | 104 |
About Andrea Cavalli
Andrea Cavalli is a scholar working on Computational Theory and Mathematics, Pharmacology and Molecular Biology, having authored 309 papers that have together received 14.9k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (85 papers), Protein Structure and Dynamics (55 papers) and Cholinesterase and Neurodegenerative Diseases (55 papers). The work is most often cited by research in Computational Theory and Mathematics (4.6k citations), Pharmacology (4.6k citations) and Toxicology (546 citations). Andrea Cavalli has collaborated with scholars based in Italy, Switzerland and United States. Frequent co-authors include Maurizio Recanatini, María Laura Bolognesi, Matteo Masetti, Giovanni Bottegoni, Marco De Vivo, Carlo Melchiorre, Vincenza Andrisano, Michela Rosini, Manuela Bartolini and Sergio Decherchi. 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.