Pierre Faux

748 total citations
20 papers, 262 citations indexed

About

Pierre Faux is a scholar working on Genetics, Plant Science and Molecular Biology. According to data from OpenAlex, Pierre Faux has authored 20 papers receiving a total of 262 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Genetics, 6 papers in Plant Science and 4 papers in Molecular Biology. Recurrent topics in Pierre Faux's work include Genetic and phenotypic traits in livestock (11 papers), Genetic Mapping and Diversity in Plants and Animals (9 papers) and Plant and animal studies (3 papers). Pierre Faux is often cited by papers focused on Genetic and phenotypic traits in livestock (11 papers), Genetic Mapping and Diversity in Plants and Animals (9 papers) and Plant and animal studies (3 papers). Pierre Faux collaborates with scholars based in Belgium, France and Brazil. Pierre Faux's co-authors include Tom Druet, Naveen Kumar Kadri, Chad Harland, Carole Charlier, Nicolas Gengler, Wouter Coppieters, Richard Spelman, Armando Caballero, Latifa Karim and Setegn Worku Alemu and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Genome Research.

In The Last Decade

Pierre Faux

17 papers receiving 261 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pierre Faux Belgium 7 230 74 50 37 24 20 262
Chuanyu Sun United States 5 296 1.3× 124 1.7× 60 1.2× 51 1.4× 38 1.6× 10 330
Irene Cardinali Italy 10 163 0.7× 46 0.6× 70 1.4× 14 0.4× 15 0.6× 23 256
Yanling Ren China 7 168 0.7× 42 0.6× 65 1.3× 82 2.2× 42 1.8× 23 267
Jesse L. Hoff United States 9 172 0.7× 34 0.5× 62 1.2× 57 1.5× 39 1.6× 12 223
Gertrud Grilz-Seger Austria 8 239 1.0× 26 0.4× 33 0.7× 26 0.7× 17 0.7× 18 284
Ulrike Ober Germany 5 450 2.0× 238 3.2× 54 1.1× 66 1.8× 38 1.6× 6 497
Dahui Huang China 12 172 0.7× 171 2.3× 111 2.2× 48 1.3× 79 3.3× 21 388
Xuelei Dai China 10 152 0.7× 108 1.5× 143 2.9× 28 0.8× 20 0.8× 16 294
Jingfang Si China 7 96 0.4× 20 0.3× 53 1.1× 34 0.9× 46 1.9× 16 167
Alexander Burren Switzerland 9 195 0.8× 25 0.3× 20 0.4× 47 1.3× 42 1.8× 19 251

Countries citing papers authored by Pierre Faux

Since Specialization
Citations

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

Fields of papers citing papers by Pierre Faux

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pierre Faux

This figure shows the co-authorship network connecting the top 25 collaborators of Pierre Faux. A scholar is included among the top collaborators of Pierre Faux 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 Pierre Faux. Pierre Faux 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.
Martínez, María Cecilia, Pierre Faux, Kaustubh Adhikari, et al.. (2025). DNA-based prediction of eye color in Latin American population applying Machine Learning models. Computers in Biology and Medicine. 194. 110404–110404.
2.
Abi‐Rached, Laurent, Pierre Faux, Julien Paganini, et al.. (2025). HLA Class Ib and MICA/MICB Expression in Human Tissues and Cell Types: Reshuffling Immune Players. HLA. 106(3). e70390–e70390. 1 indexed citations
3.
Leroy, Thibault, et al.. (2024). Inferring Long-Term and Short-Term Determinants of Genetic Diversity in Honey Bees: Beekeeping Impact and Conservation Strategies. Molecular Biology and Evolution. 41(12). 4 indexed citations
4.
Faux, Pierre, et al.. (2023). Population Genomics of the Critically Endangered Brazilian Merganser. Animals. 13(24). 3759–3759.
5.
Palombo, Valentino, et al.. (2023). Natural clines and human management impact the genetic structure of Algerian honey bee populations. Genetics Selection Evolution. 55(1). 94–94. 1 indexed citations
6.
Paganini, Julien, et al.. (2023). HLA‐F transcriptional and protein differential expression according to its genetic polymorphisms. HLA. 102(5). 578–589. 3 indexed citations
7.
Williams, Paul H., et al.. (2022). Biogeography and Diversification of Bumblebees (Hymenoptera: Apidae), with Emphasis on Neotropical Species. Diversity. 14(4). 238–238. 9 indexed citations
8.
Condémi, Silvana, Stéphane Mazières, Pierre Faux, et al.. (2021). Blood groups of Neandertals and Denisova decrypted. PLoS ONE. 16(7). e0254175–e0254175. 5 indexed citations
9.
Alemu, Setegn Worku, Naveen Kumar Kadri, Chad Harland, et al.. (2020). An evaluation of inbreeding measures using a whole-genome sequenced cattle pedigree. Heredity. 126(3). 410–423. 55 indexed citations
10.
Faux, Pierre, et al.. (2020). Fast genomic analysis of aquatic bird populations from short single-end reads considering sex-related pitfalls. Ecological Informatics. 56. 101058–101058. 1 indexed citations
11.
Faux, Pierre, Pierre Geurts, & Tom Druet. (2019). A Random Forests Framework for Modeling Haplotypes as Mosaics of Reference Haplotypes. Frontiers in Genetics. 10. 562–562. 3 indexed citations
12.
Solé, Marina, Ann-Stephan Gori, Pierre Faux, et al.. (2017). Age-based partitioning of individual genomic inbreeding levels in Belgian Blue cattle. Genetics Selection Evolution. 49(1). 92–92. 39 indexed citations
13.
Faux, Pierre & Tom Druet. (2017). A strategy to improve phasing of whole-genome sequenced individuals through integration of familial information from dense genotype panels. Genetics Selection Evolution. 49(1). 46–46. 3 indexed citations
14.
Kadri, Naveen Kumar, Chad Harland, Pierre Faux, et al.. (2016). Coding and noncoding variants in HFM1, MLH3, MSH4, MSH5, RNF212, and RNF212B affect recombination rate in cattle. Genome Research. 26(10). 1323–1332. 56 indexed citations
15.
Charlier, Carole, Wanbo Li, Chad Harland, et al.. (2016). NGS-based reverse genetic screen for common embryonic lethal mutations compromising fertility in livestock. Genome Research. 26(10). 1333–1341. 58 indexed citations
16.
Faux, Pierre & Nicolas Gengler. (2015). A method to approximate the inverse of a part of the additive relationship matrix. Journal of Animal Breeding and Genetics. 132(3). 229–238. 2 indexed citations
17.
Faux, Pierre & Nicolas Gengler. (2014). A review of inversion techniques related to the use of relationship matrices in animal breeding. SHILAP Revista de lepidopterología.
18.
Faux, Pierre, et al.. (2014). Estimation of dominance variance for live body weight in a crossbred population of pigs1. Journal of Animal Science. 92(10). 4313–4318. 4 indexed citations
19.
Faux, Pierre & Nicolas Gengler. (2013). Inversion of a part of the numerator relationship matrix using pedigree information. Genetics Selection Evolution. 45(1). 45–45. 7 indexed citations
20.
Faux, Pierre, Nicolas Gengler, & I. Misztal. (2012). A recursive algorithm for decomposition and creation of the inverse of the genomic relationship matrix. Journal of Dairy Science. 95(10). 6093–6102. 11 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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