Frédéric Burdet

2.7k total citations · 2 hit papers
17 papers, 1.7k citations indexed

About

Frédéric Burdet is a scholar working on Molecular Biology, Cancer Research and Physiology. According to data from OpenAlex, Frédéric Burdet has authored 17 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 6 papers in Cancer Research and 3 papers in Physiology. Recurrent topics in Frédéric Burdet's work include RNA modifications and cancer (5 papers), Cancer-related molecular mechanisms research (5 papers) and RNA Research and Splicing (3 papers). Frédéric Burdet is often cited by papers focused on RNA modifications and cancer (5 papers), Cancer-related molecular mechanisms research (5 papers) and RNA Research and Splicing (3 papers). Frédéric Burdet collaborates with scholars based in Switzerland, Australia and United Kingdom. Frédéric Burdet's co-authors include Mark Ibberson, Robert Lyle, Michele De Palma, Gregor D. Gilfillan, Caroline Baer, Mario Leonardo Squadrito, Claudio Maderna, Chris Rinsch, Anurag Singh and Patrick Aebischer and has published in prestigious journals such as Nature Communications, PLoS ONE and PLANT PHYSIOLOGY.

In The Last Decade

Frédéric Burdet

16 papers receiving 1.6k citations

Hit Papers

Endogenous RNAs Modulate MicroRNA Sorting to Exosomes and... 2014 2026 2018 2022 2014 2019 100 200 300 400

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Frédéric Burdet Switzerland 15 1.1k 727 176 166 140 17 1.7k
Yuanfei Zhou China 24 742 0.7× 202 0.3× 149 0.8× 179 1.1× 76 0.5× 50 1.5k
Tingting Fang China 26 825 0.7× 312 0.4× 65 0.4× 127 0.8× 96 0.7× 82 1.6k
Carolina de la Torre Spain 20 795 0.7× 188 0.3× 131 0.7× 104 0.6× 60 0.4× 51 1.4k
Hui Sun China 20 1.2k 1.0× 436 0.6× 68 0.4× 86 0.5× 62 0.4× 54 1.7k
Chi-Meng Tzeng China 20 800 0.7× 228 0.3× 58 0.3× 92 0.6× 108 0.8× 63 1.4k
Xiaojing Song China 23 596 0.5× 290 0.4× 112 0.6× 94 0.6× 97 0.7× 57 1.3k
Shaohua Yang China 21 585 0.5× 201 0.3× 67 0.4× 82 0.5× 107 0.8× 74 1.3k
Qi Ma China 23 683 0.6× 238 0.3× 83 0.5× 219 1.3× 72 0.5× 51 1.4k
Arkadiusz Orzechowski Poland 23 850 0.7× 252 0.3× 73 0.4× 200 1.2× 49 0.3× 78 1.6k

Countries citing papers authored by Frédéric Burdet

Since Specialization
Citations

This map shows the geographic impact of Frédéric Burdet'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 Frédéric Burdet with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Frédéric Burdet more than expected).

Fields of papers citing papers by Frédéric Burdet

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Frédéric Burdet. 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 Frédéric Burdet. The network helps show where Frédéric Burdet may publish in the future.

Co-authorship network of co-authors of Frédéric Burdet

This figure shows the co-authorship network connecting the top 25 collaborators of Frédéric Burdet. A scholar is included among the top collaborators of Frédéric Burdet based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Frédéric Burdet. Frédéric Burdet is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

17 of 17 papers shown
1.
Barreiro, Karina, Abigail C. Lay, Germán Leparc, et al.. (2023). An in vitro approach to understand contribution of kidney cells to human urinary extracellular vesicles. Journal of Extracellular Vesicles. 12(2). e12304–e12304. 22 indexed citations
2.
Lundgaard, Agnete Troen, Frédéric Burdet, David Westergaard, et al.. (2023). BALDR: A Web-based platform for informed comparison and prioritization of biomarker candidates for type 2 diabetes mellitus. PLoS Computational Biology. 19(8). e1011403–e1011403.
3.
Bosmani, Cristina, Florence Leuba, Nabil Hanna, et al.. (2020). Vacuolins and myosin VII are required for phagocytic uptake and phagosomal membrane recycling in Dictyostelium discoideum. Journal of Cell Science. 133(13). 2 indexed citations
4.
Mantel, Irmela, Jacopo Guidotti, Patrice Waridel, et al.. (2020). Molecular Biomarkers of Neovascular Age-Related Macular Degeneration With Incomplete Response to Anti-Vascular Endothelial Growth Factor Treatment. Frontiers in Pharmacology. 11. 594087–594087. 14 indexed citations
5.
Lamrabet, Otmane, Astrid Melotti, Frédéric Burdet, et al.. (2020). Transcriptional Responses of Dictyostelium discoideum Exposed to Different Classes of Bacteria. Frontiers in Microbiology. 11. 410–410. 14 indexed citations
6.
Andreux, Pénélope A., William Blanco-Bose, Dongryeol Ryu, et al.. (2019). The mitophagy activator urolithin A is safe and induces a molecular signature of improved mitochondrial and cellular health in humans. Nature Metabolism. 1(6). 595–603. 391 indexed citations breakdown →
7.
Jan, Maxime, Yann Emmenegger, Nicolas Guex, et al.. (2018). A systems genetics resource and analysis of sleep regulation in the mouse. PLoS Biology. 16(8). e2005750–e2005750. 36 indexed citations
8.
Motterle, Anna, Sonia Gattesco, Marie‐Line Peyot, et al.. (2017). Identification of islet-enriched long non-coding RNAs contributing to β-cell failure in type 2 diabetes. Molecular Metabolism. 6(11). 1407–1418. 51 indexed citations
9.
Alexanian, Michael, Marco Mina, Clayton E. Friedman, et al.. (2017). A transcribed enhancer dictates mesendoderm specification in pluripotency. Nature Communications. 8(1). 1806–1806. 47 indexed citations
10.
Leiba, Jade, Anna Marchetti, Wanessa C Lima, et al.. (2017). Vps13F links bacterial recognition and intracellular killing inDictyostelium. Cellular Microbiology. 19(7). e12722–e12722. 23 indexed citations
11.
Picard, Alexandre, Xavier Berney, David Tarussio, et al.. (2016). A Genetic Screen Identifies Hypothalamic Fgf15 as a Regulator of Glucagon Secretion. Cell Reports. 17(7). 1795–1806. 28 indexed citations
12.
Ounzain, Samir, Frédéric Burdet, Mark Ibberson, & Thierry Pedrazzini. (2015). Discovery and functional characterization of cardiovascular long noncoding RNAs. Journal of Molecular and Cellular Cardiology. 89. 17–26. 48 indexed citations
13.
Ounzain, Samir, Rudi Micheletti, Frédéric Burdet, et al.. (2014). Functional importance of cardiac enhancer-associated noncoding RNAs in heart development and disease. Journal of Molecular and Cellular Cardiology. 76. 55–70. 96 indexed citations
14.
Ounzain, Samir, R. Micheletti, Tim Beckmann, et al.. (2014). Genome-wide profiling of the cardiac transcriptome after myocardial infarction identifies novel heart-specific long non-coding RNAs. European Heart Journal. 36(6). 353–368. 214 indexed citations
15.
Squadrito, Mario Leonardo, Caroline Baer, Frédéric Burdet, et al.. (2014). Endogenous RNAs Modulate MicroRNA Sorting to Exosomes and Transfer to Acceptor Cells. Cell Reports. 8(5). 1432–1446. 493 indexed citations breakdown →
16.
Hauser, Philippe M., Frédéric Burdet, Ousmane H. Cissé, et al.. (2010). Comparative Genomics Suggests that the Fungal Pathogen Pneumocystis Is an Obligate Parasite Scavenging Amino Acids from Its Host's Lungs. PLoS ONE. 5(12). e15152–e15152. 39 indexed citations

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.

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