Arnaud Augert
Impact in
- Aging top 5%
- Genetics, Aging, and Longevity in Model Organisms
- Physiology top 2%
- Telomeres, Telomerase, and Senescence
Papers in
- Physiology 13
- Telomeres, Telomerase, and Senescence 13
- Oncology 7
- Lung Cancer Research Studies 6
- Co-authors
- David Bernard (16 shared papers)Jesús Gil (4 shared papers)Marco Da Costa (3 shared papers)Eva Hernando (1 shared paper)Ana Banito (1 shared paper)Jonathan Melamed (1 shared paper)Marzia Fumagalli (1 shared paper)María V. Guijarro (1 shared paper)
- Journals
- Cancer Research (3 papers)Aging (2 papers)Oncogene (2 papers)Cancer Cell (2 papers)Nature Communications (1 paper)
- Partner nations
- FranceUnited StatesUnited Kingdom
In The Last Decade
Arnaud Augert
24 papers receiving 2.7k citations
Arnaud Augert's Hit Papers
Peers
Comparison fields: 5 of 82
- Aging 79
- Physiology 1.1k
- Oncology 553
- Cancer Research 143
- Molecular Biology 626
Countries citing papers authored by Arnaud Augert
This map shows the geographic impact of Arnaud Augert'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 Arnaud Augert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Arnaud Augert more than expected).
Fields of papers citing papers by Arnaud Augert
This network shows the impact of papers produced by Arnaud Augert. 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 Arnaud Augert. The network helps show where Arnaud Augert may publish in the future.
Co-authors
The 25 scholars most cited alongside Arnaud Augert, 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 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Chemokine Signaling via the CXCR2 Receptor Reinforces Senescence Hit paper breakdown → | 2008 | 1499 |
| 2 | 2014 | 188 | |
| 3 | 2019 | 183 | |
| 4 | 2018 | 132 | |
| 5 | 2009 | 117 | |
| 6 | 2014 | 107 | |
| 7 | 2009 | 95 | |
| 8 | 2016 | 80 | |
| 9 | 2020 | 58 | |
| 10 | 2013 | 56 | |
| 11 | 2013 | 46 | |
| 12 | 2013 | 34 | |
| 13 | 2014 | 33 | |
| 14 | 2013 | 23 | |
| 15 | 2016 | 22 | |
| 16 | 2014 | 19 | |
| 17 | 2009 | 14 | |
| 18 | 2025 | 8 | |
| 19 | 2013 | 5 | |
| 20 | 2013 | 5 |
About Arnaud Augert
Arnaud Augert is a scholar working on Physiology, Oncology, Molecular Biology, Nephrology and Cancer Research, having authored 24 papers that have together received 2.7k indexed citations. Recurring topics across this work include Telomeres, Telomerase, and Senescence (13 papers), Lung Cancer Research Studies (6 papers), Mitochondrial Function and Pathology (3 papers), Cancer, Hypoxia, and Metabolism (1 paper), Cell death mechanisms and regulation (1 paper), Renal Diseases and Glomerulopathies (1 paper), Metabolism, Diabetes, and Cancer (1 paper) and Estrogen and related hormone effects (1 paper). The work is most often cited by research in Aging (79 citations), Physiology (1.1k citations), Oncology (553 citations), Cancer Research (143 citations) and Molecular Biology (626 citations). Arnaud Augert has collaborated with scholars based in France, United States and United Kingdom. Frequent co-authors include David Bernard, Jesús Gil, Marco Da Costa, Eva Hernando, Ana Banito, Jonathan Melamed, Marzia Fumagalli, María V. Guijarro, Juan Carlos Acosta and Selina Raguz. Their work appears in journals such as Cancer Research, Aging, Oncogene, Cancer Cell and Nature Communications.
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.