David Bernard
Impact in
- Aging top 0.5%
- Cancer Research top 1%
- MicroRNA in disease regulation
Papers in
- Physiology 49
- Telomeres, Telomerase, and Senescence 49
- Immunology 29
- Neutrophil, Myeloperoxidase and Oxidative Mechanisms 13
- Co-authors
- Jesús Gil (14 shared papers)Yvan de Launoit (8 shared papers)Arnaud Augert (16 shared papers)François Fuks (3 shared papers)Rachel Deplus (2 shared papers)Luciano Di Croce (2 shared papers)Carmen Brenner (2 shared papers)Nadine Martin (27 shared papers)
- Journals
- Aging Cell (10 papers)Cancer Research (8 papers)Nature Communications (5 papers)Aging (5 papers)Oncogene (4 papers)
- Partner nations
- FranceUnited KingdomUnited States
In The Last Decade
David Bernard
127 papers receiving 8.4k citations
David Bernard's Hit Papers
Peers
Comparison fields: 5 of 144
- Aging 329
- Cancer Research 1.3k
- Physiology 1.8k
- Molecular Biology 5.1k
- Immunology 1.2k
Countries citing papers authored by David Bernard
This map shows the geographic impact of David Bernard'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 David Bernard with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Bernard more than expected).
Fields of papers citing papers by David Bernard
This network shows the impact of papers produced by David Bernard. 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 David Bernard. The network helps show where David Bernard may publish in the future.
Co-authors
The 25 scholars most cited alongside David Bernard, 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 136 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | The Polycomb group protein EZH2 directly controls DNA methylation Hit paper breakdown → | 2005 | 1801 |
| 2 | Chemokine Signaling via the CXCR2 Receptor Reinforces Senescence Hit paper breakdown → | 2008 | 1486 |
| 3 | 2004 | 348 | |
| 4 | 2007 | 292 | |
| 5 | 2003 | 265 | |
| 6 | 2014 | 187 | |
| 7 | 2018 | 169 | |
| 8 | 2003 | 169 | |
| 9 | 2003 | 168 | |
| 10 | 2021 | 154 | |
| 11 | 2017 | 153 | |
| 12 | 2005 | 127 | |
| 13 | 2007 | 122 | |
| 14 | 2009 | 116 | |
| 15 | 2022 | 105 | |
| 16 | 2001 | 105 | |
| 17 | 2005 | 104 | |
| 18 | 2017 | 101 | |
| 19 | 2009 | 97 | |
| 20 | 2009 | 96 |
About David Bernard
David Bernard is a scholar working on Physiology, Immunology, Molecular Biology, Cancer Research and Oncology, having authored 136 papers that have together received 8.5k indexed citations. Recurring topics across this work include Telomeres, Telomerase, and Senescence (49 papers), Neutrophil, Myeloperoxidase and Oxidative Mechanisms (13 papers), Retinoids in leukemia and cellular processes (10 papers), Epigenetics and DNA Methylation (10 papers), Autophagy in Disease and Therapy (9 papers), DNA Repair Mechanisms (9 papers), NF-κB Signaling Pathways (8 papers) and RNA modifications and cancer (7 papers). The work is most often cited by research in Aging (329 citations), Cancer Research (1.3k citations), Physiology (1.8k citations), Molecular Biology (5.1k citations) and Immunology (1.2k citations). David Bernard has collaborated with scholars based in France, United Kingdom and United States. Frequent co-authors include Jesús Gil, Yvan de Launoit, Arnaud Augert, François Fuks, Rachel Deplus, Luciano Di Croce, Carmen Brenner, Nadine Martin, David Beach and Mario Fernández Fraga. Their work appears in journals such as Aging Cell, Cancer Research, Nature Communications, Aging and Oncogene.
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.