Daniela Fera
Impact in
- Virology top 2%
- HIV Research and Treatment
- Infectious Diseases top 2%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
- SARS-CoV-2 detection and testing
Papers in
- Virology 9
- HIV Research and Treatment 9
-
- Monoclonal and Polyclonal Antibodies Research 7
- Co-authors
- Kaiming Tao (1 shared paper)Sergei L. Kosakovsky Pond (1 shared paper)Janin Nouhin (1 shared paper)Robert Shafer (1 shared paper)Ravindra K. Gupta (1 shared paper)Tulio de Oliveira (1 shared paper)Philip L. Tzou (1 shared paper)Emma Parker Miller (2 shared papers)
- Journals
- Cell (2 papers)Nature Communications (2 papers)Viruses (2 papers)Science Translational Medicine (1 paper)Nature Reviews Genetics (1 paper)
- Partner nations
- United StatesSouth AfricaPoland
In The Last Decade
Daniela Fera
14 papers receiving 1.4k citations
Daniela Fera's Hit Papers
Peers
Comparison fields: 5 of 90
- Virology 435
- Infectious Diseases 783
- Immunology 338
- Modeling and Simulation 58
- Radiology, Nuclear Medicine and Imaging 256
Countries citing papers authored by Daniela Fera
This map shows the geographic impact of Daniela Fera'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 Daniela Fera with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniela Fera more than expected).
Fields of papers citing papers by Daniela Fera
This network shows the impact of papers produced by Daniela Fera. 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 Daniela Fera. The network helps show where Daniela Fera may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniela Fera, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | The biological and clinical significance of emerging SARS-CoV-2 variants Hit paper breakdown → | 2021 | 760 |
| 2 | 2017 | 179 | |
| 3 | 2017 | 120 | |
| 4 | 2021 | 67 | |
| 5 | 2017 | 63 | |
| 6 | 2014 | 59 | |
| 7 | 2021 | 50 | |
| 8 | 2015 | 41 | |
| 9 | 2017 | 36 | |
| 10 | 2018 | 22 | |
| 11 | 2020 | 14 | |
| 12 | 2021 | 14 | |
| 13 | 2020 | 10 | |
| 14 | 2020 | 4 |
About Daniela Fera
Daniela Fera is a scholar working on Virology, Radiology, Nuclear Medicine and Imaging, Immunology, Molecular Biology and Infectious Diseases, having authored 14 papers that have together received 1.4k indexed citations. Recurring topics across this work include HIV Research and Treatment (9 papers), Monoclonal and Polyclonal Antibodies Research (7 papers), Glycosylation and Glycoproteins Research (4 papers), Immune Cell Function and Interaction (3 papers), vaccines and immunoinformatics approaches (2 papers), SARS-CoV-2 and COVID-19 Research (2 papers), T-cell and B-cell Immunology (2 papers) and Viral gastroenteritis research and epidemiology (1 paper). The work is most often cited by research in Virology (435 citations), Infectious Diseases (783 citations), Immunology (338 citations), Modeling and Simulation (58 citations) and Radiology, Nuclear Medicine and Imaging (256 citations). Daniela Fera has collaborated with scholars based in United States, South Africa and Poland. Frequent co-authors include Kaiming Tao, Sergei L. Kosakovsky Pond, Janin Nouhin, Robert Shafer, Ravindra K. Gupta, Tulio de Oliveira, Philip L. Tzou, Emma Parker Miller, Aaron G. Schmidt and Stephen C. Harrison. Their work appears in journals such as Cell, Nature Communications, Viruses, Science Translational Medicine and Nature Reviews Genetics.
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.