Domenico Rosa
- Hepatology top 0.2%
- Epidemiology top 1%
- Radiology, Nuclear Medicine and Imaging top 1%
- Immunology top 5%
- Molecular Biology
- Co-authors
- Sergio AbrignaniMichael HoughtonSusanna CampagnoliPiero PileriGuido GrandiRoberto PetraccaFabiana FalugiG. Galli
- Topics
- Hepatitis C virus research (22 papers)Hepatitis B Virus Studies (12 papers)Monoclonal and Polyclonal Antibodies Research (9 papers)
- Cited by
- HepatologyVirologyEpidemiology
- Partner nations
- ItalyUnited StatesSwitzerland
In The Last Decade
Domenico Rosa
31 papers receiving 3.6k citations
Hit Papers
Peers
Comparison fields: 5 of 94
- Hepatology 2.7k
- Epidemiology 2.1k
- Radiology, Nuclear Medicine and Imaging 957
- Immunology 545
- Molecular Biology 497
Countries citing papers authored by Domenico Rosa
This map shows the geographic impact of Domenico Rosa'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 Rosa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Domenico Rosa more than expected).
Fields of papers citing papers by Domenico Rosa
This network shows the impact of papers produced by Domenico Rosa. 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 Rosa. The network helps show where Domenico Rosa may publish in the future.
Co-authorship network of co-authors of Domenico Rosa
This figure shows the co-authorship network connecting the top 25 collaborators of Domenico Rosa. A scholar is included among the top collaborators of Domenico Rosa 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 Rosa. Domenico Rosa is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Type 1 and 2 mouse spleen conventional dendritic cells differentially prime T helper cells after antigen targeting via DEC205 and DCIR2 receptors | 1 |
| 2 | 37 | |
| 3 | 4 | |
| 4 | 9 | |
| 5 | 193 | |
| 6 | 18 | |
| 7 | 38 | |
| 8 | HCV can activate B cells via CD81 engagement: a molecular mechanism for B cell autoreactivity and crioglobulinemia in HCV infection | 6 |
| 9 | 2 | |
| 10 | 1 | |
| 11 | 116 | |
| 12 | 68 | |
| 13 | 144 | |
| 14 | 18 | |
| 15 | 66 | |
| 16 | 53 | |
| 17 | A quantitative test to estimate neutralizing antibodies to the hepatitis C virus: cytofluorimetric assessment of envelope glycoprotein 2 binding to target cells.breakdown → | 305 |
| 18 | 115 | |
| 19 | 10 | |
| 20 | 15 |
About Domenico Rosa
Domenico Rosa is a scholar working on Hepatology, Epidemiology and Radiology, Nuclear Medicine and Imaging, having authored 31 papers that have together received 3.7k indexed citations. Recurring topics across this work include Hepatitis C virus research (22 papers), Hepatitis B Virus Studies (12 papers) and Monoclonal and Polyclonal Antibodies Research (9 papers). The work is most often cited by research in Hepatology (2.7k citations), Virology (309 citations) and Epidemiology (2.1k citations). Domenico Rosa has collaborated with scholars based in Italy, United States and Switzerland. Frequent co-authors include Sergio Abrignani, Michael Houghton, Susanna Campagnoli, Piero Pileri, Guido Grandi, Roberto Petracca, Fabiana Falugi, G. Galli, Amy J. Weiner and Yasushi Uematsu. Their work appears in journals such as Science, Proceedings of the National Academy of Sciences and The Journal of Immunology.
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.