Frédéric Brunet

61 papers receiving 3.4k citations

Frédéric Brunet's Hit Papers

Continuous streamflow prediction in ungauged basins: long short-term memory neural networks clearly outperform traditional hydrological models 2023 · 137 citations
1370+1+2Years since publication4080120

Peers

Frédéric Brunet
Comparison fields: 5 of 132
  • Physiology 201
  • Aging 51
  • Genetics 723
  • Geochemistry and Petrology 155
  • Molecular Biology 1.5k
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Colin Brownlee United Kingdom
Li Zhou China
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Countries citing papers authored by Frédéric Brunet

Since Specialization
Citations

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

Fields of papers citing papers by Frédéric Brunet

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Frédéric Brunet, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Frédéric Brunet Line = papers co-authored together Frédéric Brunet links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 61 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006308
2 2004255
3 2009197
4 2008180
5
Continuous streamflow prediction in ungauged basins: long short-term memory neural networks clearly outperform traditional hydrological models
Hit paper breakdown →
2023137
6 2014119
7 2002110
8 2008103
9 2006101
10 2009100
11 200598
12 200594
13 200490
14 200287
15 202379
16 200976
17 200875
18 200672
19 201270
20 200870

About Frédéric Brunet

Frédéric Brunet is a scholar working on Molecular Biology, Plant Science, Genetics, Ecology and Geochemistry and Petrology, having authored 61 papers that have together received 3.4k indexed citations. Recurring topics across this work include Chromosomal and Genetic Variations (16 papers), Genomics and Phylogenetic Studies (13 papers), Genetic and Clinical Aspects of Sex Determination and Chromosomal Abnormalities (10 papers), Groundwater and Isotope Geochemistry (6 papers), Reproductive biology and impacts on aquatic species (6 papers), Geology and Paleoclimatology Research (5 papers), RNA and protein synthesis mechanisms (5 papers) and Neurobiology and Insect Physiology Research (4 papers). The work is most often cited by research in Physiology (201 citations), Aging (51 citations), Genetics (723 citations), Geochemistry and Petrology (155 citations) and Molecular Biology (1.5k citations). Frédéric Brunet has collaborated with scholars based in France, United States and Germany. Frequent co-authors include Vincent Laudet, Jean‐Nicolas Volff, Marc Robinson‐Rechavi, Manyuan Long, Jean‐Luc Probst, Mathilde Paris, Héctor Escrivá, Stéphanie Bertrand, Hugues Roest Crollius and Gilles Parmentier. Their work appears in journals such as Journal of Molecular Evolution, Proceedings of the National Academy of Sciences, PLoS Genetics, BMC Evolutionary Biology and Molecular Biology and Evolution.

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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