Mathieu Emily

789 citations
26 papers · 480 · h-index 10

Impact in

    • Virtual Reality Applications and Impacts
    • Genetic Associations and Epidemiology
    • Genetic Mapping and Diversity in Plants and Animals

Papers in

    • Bioinformatics and Genomic Networks 4
    • Genetic Associations and Epidemiology 7
    • Genetic Mapping and Diversity in Plants and Animals 3

Mathieu Emily

23 papers receiving 474 citations

Peers

Mathieu Emily
Comparison fields: 5 of 109
  • Human-Computer Interaction 92
  • Genetics 125
  • Nutrition and Dietetics 54
  • Molecular Biology 224
  • Cognitive Neuroscience 62
Replace Yoko Yoshida with:
Yoko Yoshida Japan
Yiru Shen China
Mengmeng Han China
Antoine Marin France
Sainan Zhao China
Fuchs Germany
Yuan Jin China
Taeheon Lee South Korea
Mitsuru Murakami Japan
Gerardo González United States
Mathieu Emily relative to Yoko Yoshida Japan Yoko Yoshida's profile →
Citations per field
00.5×3.0×
Yoko Yoshida · 1×
Citations per year

Countries citing papers authored by Mathieu Emily

Since Specialization
Citations

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

Fields of papers citing papers by Mathieu Emily

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009109
2 2013101
3 201062
4 201841
5 201028
6 202124
7 201623
8 201513
9 201811
10 201211
11 20219
12 20228
13 20168
14 20177
15 20075
16 20204
17 20243
18 20163
19 20043
20 20222

About Mathieu Emily

Mathieu Emily is a scholar working on Molecular Biology, Genetics, Epidemiology, Physiology and Human-Computer Interaction, having authored 26 papers that have together received 480 indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (7 papers), Bioinformatics and Genomic Networks (4 papers), Genetic Mapping and Diversity in Plants and Animals (3 papers), Virtual Reality Applications and Impacts (2 papers), Infant Nutrition and Health (2 papers), Genetics and Plant Breeding (2 papers), Breastfeeding Practices and Influences (2 papers) and Physical Activity and Health (2 papers). The work is most often cited by research in Human-Computer Interaction (92 citations), Genetics (125 citations), Nutrition and Dietetics (54 citations), Molecular Biology (224 citations) and Cognitive Neuroscience (62 citations). Mathieu Emily has collaborated with scholars based in France, Denmark and Germany. Frequent co-authors include Christian Delamarche, Mikkel Heide Schierup, Thomas Mailund, Jotun Hein, Maud Marchal, Anatole Lécuyer, Franck Multon, Bruno Arnaldi, Amélie Deglaire and Claire Bourlieu‐Lacanal. Their work appears in journals such as Statistical Methods in Medical Research, IEEE Transactions on Haptics, PLoS ONE, Electrophoresis and European Journal of Human Genetics.

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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