Sèverine Bérard

462 citations
15 papers · 169 · h-index 8

Impact in

    • Genome Rearrangement Algorithms
    • Genetic diversity and population structure
    • Genomics and Phylogenetic Studies
    • RNA and protein synthesis mechanisms
    • DNA and Biological Computing
    • Bioinformatics and Genomic Networks

Papers in

    • Genomics and Phylogenetic Studies 8
    • DNA and Biological Computing 2
    • Genetics, Bioinformatics, and Biomedical Research 1
    • Genome Rearrangement Algorithms 6
    • Genomic variations and chromosomal abnormalities 3

Sèverine Bérard

15 papers receiving 164 citations

Peers

Sèverine Bérard
Comparison fields: 5 of 49
  • Genetics 98
  • Molecular Biology 116
  • Plant Science 59
  • Artificial Intelligence 39
  • Toxicology 4
Replace Manuel Lafond with:
Manuel Lafond Canada
T. D. P. Brunet Canada
M.-F. Sagot France
David A. Christie United Kingdom
Philippe Gambette France
Xinyi Shi China
Roland Wittler Germany
Annie Château France
Camille Marchet France
Sèverine Bérard relative to Manuel Lafond Canada Manuel Lafond's profile →
Citations per field
00.5×1.5×1.9×
Manuel Lafond · 1×
Citations per year

Countries citing papers authored by Sèverine Bérard

Since Specialization
Citations

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

Fields of papers citing papers by Sèverine Bérard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Sèverine Bérard, 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 Sèverine Bérard Line = papers co-authored together Sèverine Bérard links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1 200731
2 201520
3 201219
4 200317
5 202115
6 200612
7 200911
8 20178
9 20166
10 20096
11 20076
12 20086
13 20185
14 20104
15 20023

About Sèverine Bérard

Sèverine Bérard is a scholar working on Molecular Biology, Genetics, Plant Science, Ecology and Artificial Intelligence, having authored 15 papers that have together received 169 indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (8 papers), Chromosomal and Genetic Variations (8 papers), Genome Rearrangement Algorithms (6 papers), Genomic variations and chromosomal abnormalities (3 papers), DNA and Biological Computing (2 papers), Algorithms and Data Compression (2 papers), Genetics, Bioinformatics, and Biomedical Research (1 paper) and Animal Behavior and Reproduction (1 paper). The work is most often cited by research in Genetics (98 citations), Molecular Biology (116 citations), Plant Science (59 citations), Artificial Intelligence (39 citations) and Toxicology (4 citations). Sèverine Bérard has collaborated with scholars based in France, Canada and India. Frequent co-authors include Cédric Chauve, Éric Rivals, Christophe Paul, Éric Tannier, Anne Bergeron, Annie Château, Carl Herrmann, Laurent Tichit, Vincent Daubin and Vincent Berry. Their work appears in journals such as BMC Genomics, Bioinformatics, Journal of Computational Biology, Acta Biotheoretica and BMC Bioinformatics.

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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