Anne Ricard

1.5k total citations
55 papers, 933 citations indexed

About

Anne Ricard is a scholar working on Genetics, Equine and Cell Biology. According to data from OpenAlex, Anne Ricard has authored 55 papers receiving a total of 933 indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Genetics, 27 papers in Equine and 14 papers in Cell Biology. Recurrent topics in Anne Ricard's work include Genetic and phenotypic traits in livestock (39 papers), Veterinary Equine Medical Research (27 papers) and Genetic Mapping and Diversity in Plants and Animals (16 papers). Anne Ricard is often cited by papers focused on Genetic and phenotypic traits in livestock (39 papers), Veterinary Equine Medical Research (27 papers) and Genetic Mapping and Diversity in Plants and Animals (16 papers). Anne Ricard collaborates with scholars based in France, Morocco and Sweden. Anne Ricard's co-authors include Étienne Verrier, J. Philipsson, Andrés Legarra, E. Bruns, Cathy L. Z. DuBois, Simon Teyssèdre, Å. Viklund, E.P.C. Koenen, Thomas Druml and Gertrud Grilz-Seger and has published in prestigious journals such as PLoS ONE, Genetics and Journal of Animal Science.

In The Last Decade

Anne Ricard

51 papers receiving 900 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Anne Ricard France 20 671 433 162 153 140 55 933
Brandon D. Velie Australia 17 394 0.6× 308 0.7× 102 0.6× 78 0.5× 86 0.6× 53 627
Thomas Druml Austria 17 590 0.9× 220 0.5× 152 0.9× 62 0.4× 109 0.8× 34 837
Bertrand Langlois France 14 335 0.5× 249 0.6× 117 0.7× 100 0.7× 211 1.5× 28 618
E.P.C. Koenen Netherlands 17 861 1.3× 410 0.9× 414 2.6× 619 4.0× 124 0.9× 23 1.3k
Å. Viklund Sweden 11 266 0.4× 277 0.6× 81 0.5× 52 0.3× 68 0.5× 20 389
Beatrice A. McGivney Ireland 18 580 0.9× 350 0.8× 115 0.7× 31 0.2× 346 2.5× 33 990
L. Vostrý Czechia 14 606 0.9× 92 0.2× 178 1.1× 206 1.3× 35 0.3× 113 740
E.M. van Grevenhof Netherlands 13 191 0.3× 188 0.4× 89 0.5× 79 0.5× 36 0.3× 24 545
Maurizio Silvestrelli Italy 17 314 0.5× 226 0.5× 75 0.5× 56 0.4× 135 1.0× 43 716
B.J. Ducro Netherlands 13 173 0.3× 181 0.4× 145 0.9× 46 0.3× 40 0.3× 18 429

Countries citing papers authored by Anne Ricard

Since Specialization
Citations

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

Fields of papers citing papers by Anne Ricard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anne Ricard

This figure shows the co-authorship network connecting the top 25 collaborators of Anne Ricard. A scholar is included among the top collaborators of Anne Ricard 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 Anne Ricard. Anne Ricard is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Ricard, Anne, et al.. (2024). Population structure and genomic diversity of the Einsiedler horse. Animal Genetics. 55(3). 475–479. 1 indexed citations
2.
Mikko, Sofia, Anne Ricard, Brandon D. Velie, et al.. (2024). Using high-density SNP data to unravel the origin of the Franches-Montagnes horse breed. Genetics Selection Evolution. 56(1). 53–53. 2 indexed citations
3.
David, Ingrid & Anne Ricard. (2023). An improved transmissibility model to detect transgenerational transmitted environmental effects. Genetics Selection Evolution. 55(1). 66–66.
4.
Ricard, Anne, et al.. (2023). Genetic analysis of geometric morphometric 3D visuals of French jumping horses. Genetics Selection Evolution. 55(1). 63–63. 2 indexed citations
5.
Ricard, Anne, et al.. (2022). Copula miss-specification in REML multivariate genetic animal model estimation. Genetics Selection Evolution. 54(1). 36–36. 1 indexed citations
6.
Druml, Thomas, et al.. (2021). DPF3, A Putative Candidate Gene For Melanoma Etiopathogenesis in Gray Horses. Journal of Equine Veterinary Science. 108. 103797–103797. 7 indexed citations
7.
Ricard, Anne, et al.. (2021). Genomic Correlations Between the Gaits of Young Horses Measured by Accelerometry and Functional Longevity in Jumping Competition. Frontiers in Genetics. 12. 619947–619947. 4 indexed citations
8.
Ricard, Anne, et al.. (2020). Accelerometers Provide Early Genetic Selection Criteria for Jumping Horses. Frontiers in Genetics. 11. 448–448. 6 indexed citations
10.
Ricard, Anne, Céline Robert, Caroline Morgenthaler, et al.. (2017). Endurance Exercise Ability in the Horse: A Trait with Complex Polygenic Determinism. Frontiers in Genetics. 8. 89–89. 30 indexed citations
11.
Brochard, Charlène, Alexandra Ducancelle, Adeline Pivert, et al.. (2017). Human papillomavirus does not play a role in the Barrett esophagus: a French cohort. Diseases of the Esophagus. 30(11). 1–7. 1 indexed citations
12.
Martin, Pauline, Isabelle Palhière, Anne Ricard, Gwenola Tosser‐Klopp, & Rachel Rupp. (2016). Genome Wide Association Study Identifies New Loci Associated with Undesired Coat Color Phenotypes in Saanen Goats. PLoS ONE. 11(3). e0152426–e0152426. 35 indexed citations
13.
Legarra, Andrés, Pascal Croiseau, Marie-Pierre Sanchez, et al.. (2015). A comparison of methods for whole-genome QTL mapping using dense markers in four livestock species. Genetics Selection Evolution. 47(1). 6–6. 33 indexed citations
14.
Ricard, Anne. (2015). Does heterozygosity at the DMRT3 gene make French trotters better racers?. Genetics Selection Evolution. 47(1). 10–10. 18 indexed citations
15.
Kornaś, Sławomir, et al.. (2015). Estimation of genetic parameters for resistance to gastro-intestinal nematodes in pure blood Arabian horses. International Journal for Parasitology. 45(4). 237–242. 17 indexed citations
16.
Ricard, Anne, et al.. (2013). Genetic and environmental analysis of dystocia and stillbirths in draft horses. animal. 8(2). 184–191. 8 indexed citations
17.
Teyssèdre, Simon, Jean-Michel Elsen, & Anne Ricard. (2012). Statistical distributions of test statistics used for quantitative trait association mapping in structured populations. Genetics Selection Evolution. 44(1). 32–32. 14 indexed citations
18.
Leroy, Grégoire, et al.. (2009). Genetic diversity of a large set of horse breeds raised in France assessed by microsatellite polymorphism. Genetics Selection Evolution. 41(1). 5–5. 56 indexed citations
19.
Ricard, Anne, et al.. (1996). Analyse de la variabilité génétique de cinq races françaises de chevaux de course et de sport à partir des données généalogiques et du polymorphisme des marqueurs sanguins (probabilité d'origine des gènes, heterozygotie). HAL (Le Centre pour la Communication Scientifique Directe). 49 indexed citations
20.
Verrier, Étienne, et al.. (1996). Genetic variability within French race and riding horse breeds from genealogical data and blood marker polymorphisms. Genetics Selection Evolution. 28(1). 47 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026