Elsa Vera
Impact in
- Aging top 0.2%
- Genetics, Aging, and Longevity in Model Organisms
- Physiology top 1%
- Telomeres, Telomerase, and Senescence
Papers in
- Physiology 15
- Telomeres, Telomerase, and Senescence 15
-
- CRISPR and Genetic Engineering 2
- Muscle Physiology and Disorders 2
- Pluripotent Stem Cells Research 2
- Epigenetics and DNA Methylation 1
- Co-authors
- Marı́a A. Blasco (14 shared papers)Bruno Bernardes de Jesus (4 shared papers)Águeda M. Tejera (3 shared papers)Lorenz Studer (4 shared papers)Andrés Canela (4 shared papers)Kerstin Schneeberger (2 shared papers)Calvin B. Harley (2 shared papers)Peter Klatt (1 shared paper)
- Journals
- Cell stem cell (2 papers)Cell Reports (2 papers)Proceedings of the National Academy of Sciences (2 papers)Oncogene (1 paper)Genes & Development (1 paper)
- Partner nations
- SpainUnited StatesUnited Kingdom
In The Last Decade
Elsa Vera
19 papers receiving 3.4k citations
Elsa Vera's Hit Papers
Peers
Comparison fields: 5 of 114
- Aging 805
- Physiology 1.8k
- Developmental Neuroscience 171
- Molecular Biology 1.8k
- Biological Psychiatry 51
Countries citing papers authored by Elsa Vera
This map shows the geographic impact of Elsa Vera'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 Elsa Vera with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Elsa Vera more than expected).
Fields of papers citing papers by Elsa Vera
This network shows the impact of papers produced by Elsa Vera. 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 Elsa Vera. The network helps show where Elsa Vera may publish in the future.
Co-authors
The 25 scholars most cited alongside Elsa Vera, 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 | Human iPSC-Based Modeling of Late-Onset Disease via Progerin-Induced Aging Hit paper breakdown → | 2013 | 581 |
| 2 | 2012 | 417 | |
| 3 | 2008 | 283 | |
| 4 | 2011 | 282 | |
| 5 | 2007 | 262 | |
| 6 | 2019 | 253 | |
| 7 | 2012 | 170 | |
| 8 | 2010 | 154 | |
| 9 | 2015 | 140 | |
| 10 | 2016 | 131 | |
| 11 | 2013 | 127 | |
| 12 | 2008 | 109 | |
| 13 | 2008 | 107 | |
| 14 | 2011 | 105 | |
| 15 | 2019 | 98 | |
| 16 | 2013 | 91 | |
| 17 | 2012 | 78 | |
| 18 | 2015 | 36 | |
| 19 | 2009 | 28 |
About Elsa Vera
Elsa Vera is a scholar working on Physiology, Molecular Biology, Aging, Genetics and Immunology, having authored 19 papers that have together received 3.5k indexed citations. Recurring topics across this work include Telomeres, Telomerase, and Senescence (15 papers), Genetics, Aging, and Longevity in Model Organisms (7 papers), CRISPR and Genetic Engineering (2 papers), Muscle Physiology and Disorders (2 papers), Pluripotent Stem Cells Research (2 papers), Neurogenesis and neuroplasticity mechanisms (1 paper), Epigenetics and DNA Methylation (1 paper) and Immunotherapy and Immune Responses (1 paper). The work is most often cited by research in Aging (805 citations), Physiology (1.8k citations), Developmental Neuroscience (171 citations), Molecular Biology (1.8k citations) and Biological Psychiatry (51 citations). Elsa Vera has collaborated with scholars based in Spain, United States and United Kingdom. Frequent co-authors include Marı́a A. Blasco, Bruno Bernardes de Jesus, Águeda M. Tejera, Lorenz Studer, Andrés Canela, Kerstin Schneeberger, Calvin B. Harley, Peter Klatt, Eduard Ayuso and Fátima Bosch. Their work appears in journals such as Cell stem cell, Cell Reports, Proceedings of the National Academy of Sciences, Oncogene and Genes & Development.
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.