Domenico Benvenuto
- Infectious Diseases top 1%
- Modeling and Simulation top 0.5%
- Molecular Biology
- Radiology, Nuclear Medicine and Imaging top 5%
- Epidemiology
- Co-authors
- Massimo CiccozziSilvia AngelettiMarta GiovanettiStefano PascarellaMartina BianchiRoberto CaudaAntonio CassoneSergio Bernardini
- Topics
- SARS-CoV-2 and COVID-19 Research (21 papers)COVID-19 Clinical Research Studies (5 papers)vaccines and immunoinformatics approaches (5 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEScientific Reports
- Partner nations
- ItalyBrazilUnited States
In The Last Decade
Domenico Benvenuto
52 papers receiving 2.2k citations
Hit Papers
Peers
Comparison fields: 5 of 159
- Infectious Diseases 1.1k
- Modeling and Simulation 407
- Molecular Biology 344
- Radiology, Nuclear Medicine and Imaging 275
- Epidemiology 231
Countries citing papers authored by Domenico Benvenuto
This map shows the geographic impact of Domenico Benvenuto'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 Domenico Benvenuto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Domenico Benvenuto more than expected).
Fields of papers citing papers by Domenico Benvenuto
This network shows the impact of papers produced by Domenico Benvenuto. 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 Domenico Benvenuto. The network helps show where Domenico Benvenuto may publish in the future.
Co-authorship network of co-authors of Domenico Benvenuto
This figure shows the co-authorship network connecting the top 25 collaborators of Domenico Benvenuto. A scholar is included among the top collaborators of Domenico Benvenuto 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 Domenico Benvenuto. Domenico Benvenuto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 1 | |
| 3 | 8 | |
| 4 | 1 | |
| 5 | 3 | |
| 6 | 24 | |
| 7 | 4 | |
| 8 | 11 | |
| 9 | 2 | |
| 10 | 12 | |
| 11 | 1 | |
| 12 | 20 | |
| 13 | 3 | |
| 14 | 17 | |
| 15 | 74 | |
| 16 | 138 | |
| 17 | Application of the ARIMA model on the COVID-2019 epidemic datasetbreakdown → | 440 |
| 18 | 5 | |
| 19 | 9 | |
| 20 | 9 |
About Domenico Benvenuto
Domenico Benvenuto is a scholar working on Infectious Diseases, Modeling and Simulation and Animal Science and Zoology, having authored 53 papers that have together received 2.2k indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (21 papers), COVID-19 Clinical Research Studies (5 papers) and vaccines and immunoinformatics approaches (5 papers). The work is most often cited by research in Modeling and Simulation (407 citations), Infectious Diseases (1.1k citations) and Animal Science and Zoology (126 citations). Domenico Benvenuto has collaborated with scholars based in Italy, Brazil and United States. Frequent co-authors include Massimo Ciccozzi, Silvia Angeletti, Marta Giovanetti, Stefano Pascarella, Martina Bianchi, Roberto Cauda, Antonio Cassone, Sergio Bernardini, Caterina Sagnelli and Marco Ciotti. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.
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.