Andrea R. Beccari
- Molecular Biology
- Computational Theory and Mathematics top 1%
- Oncology top 10%
- Infectious Diseases top 5%
- Immunology top 10%
- Co-authors
- Marcello AllegrettiCarmen CerchiaCinzia BizzarriRiccardo BertiniRolando CannalireVincenzo SummaFrancesco Saverio Di LevaCarmine Talarico
- Topics
- Computational Drug Discovery Methods (24 papers)SARS-CoV-2 and COVID-19 Research (12 papers)Protein Structure and Dynamics (8 papers)
- Journals
- Proceedings of the National Academy of SciencesSHILAP Revista de lepidopterologíaBioinformatics
- Partner nations
- ItalyUnited StatesGermany
In The Last Decade
Andrea R. Beccari
54 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 132
- Molecular Biology 535
- Computational Theory and Mathematics 378
- Oncology 294
- Infectious Diseases 274
- Immunology 267
Countries citing papers authored by Andrea R. Beccari
This map shows the geographic impact of Andrea R. Beccari'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 R. Beccari with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrea R. Beccari more than expected).
Fields of papers citing papers by Andrea R. Beccari
This network shows the impact of papers produced by Andrea R. Beccari. 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 R. Beccari. The network helps show where Andrea R. Beccari may publish in the future.
Co-authorship network of co-authors of Andrea R. Beccari
This figure shows the co-authorship network connecting the top 25 collaborators of Andrea R. Beccari. A scholar is included among the top collaborators of Andrea R. Beccari 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 R. Beccari. Andrea R. Beccari 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 | 14 | |
| 4 | 17 | |
| 5 | 7 | |
| 6 | 25 | |
| 7 | 9 | |
| 8 | 5 | |
| 9 | 17 | |
| 10 | 6 | |
| 11 | 21 | |
| 12 | 35 | |
| 13 | 14 | |
| 14 | 34 | |
| 15 | 25 | |
| 16 | 26 | |
| 17 | 83 | |
| 18 | 172 | |
| 19 | 63 | |
| 20 | 75 |
About Andrea R. Beccari
Andrea R. Beccari is a scholar working on Computational Theory and Mathematics, Infectious Diseases and Sensory Systems, having authored 59 papers that have together received 1.3k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (24 papers), SARS-CoV-2 and COVID-19 Research (12 papers) and Protein Structure and Dynamics (8 papers). The work is most often cited by research in Computational Theory and Mathematics (378 citations), Infectious Diseases (274 citations) and Immunology (267 citations). Andrea R. Beccari has collaborated with scholars based in Italy, United States and Germany. Frequent co-authors include Marcello Allegretti, Carmen Cerchia, Cinzia Bizzarri, Riccardo Bertini, Rolando Cannalire, Vincenzo Summa, Francesco Saverio Di Leva, Carmine Talarico, Candida Manelfi and Matteo Lo Monte. Their work appears in journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and Bioinformatics.
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.