Arnaud Augert
Impact in
- Aging top 2%
- Genetics, Aging, and Longevity in Model Organisms
- Physiology top 2%
- Telomeres, Telomerase, and Senescence
Papers in
-
- Retinoids in leukemia and cellular processes 4
- Advanced biosensing and bioanalysis techniques 3
- DNA Repair Mechanisms 3
- Epigenetics and DNA Methylation 2
- Oncology 10
- Lung Cancer Research Studies 6
- Co-authors
- David Bernard (15 shared papers)Jesús Gil (4 shared papers)Marco Da Costa (3 shared papers)Eva Hernando (1 shared paper)María V. Guijarro (1 shared paper)Juan Carlos Acosta (1 shared paper)Yoshihiro Takatsu (1 shared paper)Marzia Fumagalli (1 shared paper)
- Journals
- Cancer Research (3 papers)Oncogene (2 papers)Cancer Cell (1 paper)Aging (1 paper)Journal of Thoracic Oncology (1 paper)
- Partner nations
- FranceUnited StatesSouth Africa
In The Last Decade
Arnaud Augert
22 papers receiving 2.4k citations
Arnaud Augert's Hit Papers
Peers
Comparison fields: 5 of 95
- Aging 122
- Physiology 880
- Immunology 603
- Oncology 680
- Cancer Research 365
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 22 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 | 1374 |
| 2 | 2014 | 173 | |
| 3 | 2019 | 154 | |
| 4 | 2018 | 115 | |
| 5 | 2009 | 107 | |
| 6 | 2014 | 98 | |
| 7 | 2009 | 88 | |
| 8 | 2016 | 73 | |
| 9 | 2013 | 52 | |
| 10 | 2020 | 51 | |
| 11 | 2013 | 42 | |
| 12 | 2014 | 31 | |
| 13 | 2013 | 30 | |
| 14 | 2013 | 22 | |
| 15 | 2016 | 19 | |
| 16 | 2009 | 12 | |
| 17 | 2021 | 9 | |
| 18 | 2015 | 5 | |
| 19 | 2013 | 5 | |
| 20 | 2025 | 3 |
About Arnaud Augert
Arnaud Augert is a scholar working on Molecular Biology, Oncology, Epidemiology, Physiology and Immunology, having authored 22 papers that have together received 2.5k indexed citations. Recurring topics across this work include Telomeres, Telomerase, and Senescence (7 papers), Lung Cancer Research Studies (6 papers), Neuroendocrine Tumor Research Advances (6 papers), Retinoids in leukemia and cellular processes (4 papers), Advanced biosensing and bioanalysis techniques (3 papers), Neutrophil, Myeloperoxidase and Oxidative Mechanisms (3 papers), DNA Repair Mechanisms (3 papers) and Epigenetics and DNA Methylation (2 papers). The work is most often cited by research in Aging (122 citations), Physiology (880 citations), Immunology (603 citations), Oncology (680 citations) and Cancer Research (365 citations). Arnaud Augert has collaborated with scholars based in France, United States and South Africa. Frequent co-authors include David Bernard, Jesús Gil, Marco Da Costa, Eva Hernando, María V. Guijarro, Juan Carlos Acosta, Yoshihiro Takatsu, Marzia Fumagalli, Jonathan Melamed and М. М. Попов. Their work appears in journals such as Cancer Research, Oncogene, Cancer Cell, Aging and Journal of Thoracic Oncology.
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.