Daniel Marrama
Impact in
- Infectious Diseases top 0.5%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
- SARS-CoV-2 detection and testing
- Modeling and Simulation top 1%
- COVID-19 epidemiological studies
Papers in
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- vaccines and immunoinformatics approaches 5
-
- SARS-CoV-2 and COVID-19 Research 2
- COVID-19 Clinical Research Studies 1
- Co-authors
- Alessandro Sette (7 shared papers)Bjoern Peters (7 shared papers)Jason Greenbaum (3 shared papers)Aaron Sutherland (2 shared papers)April Frazier (2 shared papers)Ramesh Jadi (1 shared paper)Stephen A. Rawlings (1 shared paper)Sydney I. Ramirez (1 shared paper)
- Journals
- Circulation Research (1 paper)Nucleic Acids Research (1 paper)Cancer Immunology Immunotherapy (1 paper)BMC Bioinformatics (1 paper)Cell Host & Microbe (1 paper)
- Partner nations
- United StatesDenmarkArgentina
In The Last Decade
Daniel Marrama
6 papers receiving 2.3k citations
Daniel Marrama's Hit Papers
Peers
Comparison fields: 5 of 96
- Infectious Diseases 1.9k
- Modeling and Simulation 200
- Neurology 428
- Immunology 489
- Health 121
Countries citing papers authored by Daniel Marrama
This map shows the geographic impact of Daniel Marrama'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 Daniel Marrama with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Marrama more than expected).
Fields of papers citing papers by Daniel Marrama
This network shows the impact of papers produced by Daniel Marrama. 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 Daniel Marrama. The network helps show where Daniel Marrama may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Marrama, 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 | Targets of T Cell Responses to SARS-CoV-2 Coronavirus in Humans with COVID-19 Disease and Unexposed Individuals Hit paper breakdown → | 2020 | 2282 |
| 2 | 2024 | 22 | |
| 3 | 2022 | 17 | |
| 4 | 2023 | 13 | |
| 5 | 2022 | 12 | |
| 6 | 2023 | 7 | |
| 7 | 2025 | 0 |
About Daniel Marrama
Daniel Marrama is a scholar working on Molecular Biology, Infectious Diseases, Immunology, Neurology and Radiology, Nuclear Medicine and Imaging, having authored 7 papers that have together received 2.4k indexed citations. Recurring topics across this work include vaccines and immunoinformatics approaches (5 papers), SARS-CoV-2 and COVID-19 Research (2 papers), Atherosclerosis and Cardiovascular Diseases (1 paper), COVID-19 Clinical Research Studies (1 paper), Immunotherapy and Immune Responses (1 paper), Monoclonal and Polyclonal Antibodies Research (1 paper), T-cell and B-cell Immunology (1 paper) and Bacterial Infections and Vaccines (1 paper). The work is most often cited by research in Infectious Diseases (1.9k citations), Modeling and Simulation (200 citations), Neurology (428 citations), Immunology (489 citations) and Health (121 citations). Daniel Marrama has collaborated with scholars based in United States, Denmark and Argentina. Frequent co-authors include Alessandro Sette, Bjoern Peters, Jason Greenbaum, Aaron Sutherland, April Frazier, Ramesh Jadi, Stephen A. Rawlings, Sydney I. Ramirez, Daniela Weiskopf and Shane Crotty. Their work appears in journals such as Circulation Research, Nucleic Acids Research, Cancer Immunology Immunotherapy, BMC Bioinformatics and Cell Host & Microbe.
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.