Ramiro E. Verdún
Impact in
- Aging top 1%
- Genetics, Aging, and Longevity in Model Organisms
- Physiology top 2%
- Telomeres, Telomerase, and Senescence
Papers in
-
- DNA Repair Mechanisms 12
- Epigenetics and DNA Methylation 7
- Ubiquitin and proteasome pathways 5
- Epidemiology 12
- Trypanosoma species research and implications 5
- Cytomegalovirus and herpesvirus research 5
- Co-authors
- Jan Karlseder (5 shared papers)Candy Haggblom (3 shared papers)Laure Crabbé (2 shared papers)Joaquı́n M. Espinosa (1 shared paper)Beverly M. Emerson (1 shared paper)Daniel O. Sánchez (8 shared papers)Elena M. Cortizas (8 shared papers)Javier M. Di Noia (5 shared papers)
- Journals
- Blood (4 papers)The Journal of Immunology (4 papers)Infection and Immunity (2 papers)Oncogene (2 papers)Molecular Cell (2 papers)
- Partner nations
- United StatesArgentinaCanada
In The Last Decade
Ramiro E. Verdún
45 papers receiving 2.5k citations
Peers
Comparison fields: 5 of 93
- Aging 194
- Physiology 1.0k
- Molecular Biology 1.9k
- Oncology 354
- Cancer Research 194
Countries citing papers authored by Ramiro E. Verdún
This map shows the geographic impact of Ramiro E. Verdún'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 Ramiro E. Verdún with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ramiro E. Verdún more than expected).
Fields of papers citing papers by Ramiro E. Verdún
This network shows the impact of papers produced by Ramiro E. Verdún. 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 Ramiro E. Verdún. The network helps show where Ramiro E. Verdún may publish in the future.
Co-authors
The 25 scholars most cited alongside Ramiro E. Verdún, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2004 | 495 | |
| 2 | 2007 | 389 | |
| 3 | 2006 | 269 | |
| 4 | 2005 | 232 | |
| 5 | 2003 | 211 | |
| 6 | 2018 | 148 | |
| 7 | 2008 | 106 | |
| 8 | 1998 | 55 | |
| 9 | 2019 | 51 | |
| 10 | 2014 | 46 | |
| 11 | 2013 | 43 | |
| 12 | 2020 | 39 | |
| 13 | 2016 | 38 | |
| 14 | 2001 | 37 | |
| 15 | 2016 | 35 | |
| 16 | 2018 | 35 | |
| 17 | 2016 | 25 | |
| 18 | 2011 | 24 | |
| 19 | 2021 | 22 | |
| 20 | 2015 | 18 |
About Ramiro E. Verdún
Ramiro E. Verdún is a scholar working on Molecular Biology, Epidemiology, Oncology, Immunology and Physiology, having authored 46 papers that have together received 2.5k indexed citations. Recurring topics across this work include DNA Repair Mechanisms (12 papers), Epigenetics and DNA Methylation (7 papers), T-cell and B-cell Immunology (7 papers), Immune Cell Function and Interaction (7 papers), Telomeres, Telomerase, and Senescence (6 papers), Ubiquitin and proteasome pathways (5 papers), Trypanosoma species research and implications (5 papers) and Cytomegalovirus and herpesvirus research (5 papers). The work is most often cited by research in Aging (194 citations), Physiology (1.0k citations), Molecular Biology (1.9k citations), Oncology (354 citations) and Cancer Research (194 citations). Ramiro E. Verdún has collaborated with scholars based in United States, Argentina and Canada. Frequent co-authors include Jan Karlseder, Candy Haggblom, Laure Crabbé, Joaquı́n M. Espinosa, Beverly M. Emerson, Daniel O. Sánchez, Elena M. Cortizas, Javier M. Di Noia, Daniel Karl and Jack D. Griffith. Their work appears in journals such as Blood, The Journal of Immunology, Infection and Immunity, Oncogene and Molecular Cell.
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.