André Garcia

536 total citations
33 papers, 347 citations indexed

About

André Garcia is a scholar working on Genetics, Plant Science and Animal Science and Zoology. According to data from OpenAlex, André Garcia has authored 33 papers receiving a total of 347 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Genetics, 8 papers in Plant Science and 7 papers in Animal Science and Zoology. Recurrent topics in André Garcia's work include Genetic and phenotypic traits in livestock (26 papers), Genetic Mapping and Diversity in Plants and Animals (19 papers) and Genetics and Plant Breeding (7 papers). André Garcia is often cited by papers focused on Genetic and phenotypic traits in livestock (26 papers), Genetic Mapping and Diversity in Plants and Animals (19 papers) and Genetics and Plant Breeding (7 papers). André Garcia collaborates with scholars based in United States, Brazil and Italy. André Garcia's co-authors include Daniela Lourenço, S. Tsuruta, I. Misztal, Brian G. Bosworth, Alberto Cesarani, Geoffrey C. Waldbieser, Jorge Hidalgo, Carlos López-Fanjul, N.P.P. Macciotta and Timothy D. Leeds and has published in prestigious journals such as Journal of Dairy Science, Aquaculture and Journal of Animal Science.

In The Last Decade

André Garcia

29 papers receiving 341 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
André Garcia United States 11 277 102 72 70 40 33 347
Hailiang Song China 13 420 1.5× 95 0.9× 84 1.2× 71 1.0× 43 1.1× 36 505
J. J. Tosh Canada 9 318 1.1× 49 0.5× 53 0.7× 198 2.8× 193 4.8× 17 460
A. Abinawanto Indonesia 8 130 0.5× 89 0.9× 31 0.4× 46 0.7× 24 0.6× 91 357
A M Winkelman New Zealand 10 289 1.0× 92 0.9× 85 1.2× 82 1.2× 121 3.0× 26 374
Rajesh Joshi Norway 11 226 0.8× 154 1.5× 54 0.8× 30 0.4× 12 0.3× 16 357
Tracey C. van Stijn New Zealand 10 292 1.1× 21 0.2× 109 1.5× 35 0.5× 34 0.8× 27 442
A. Hidas Hungary 11 262 0.9× 37 0.4× 92 1.3× 112 1.6× 14 0.3× 23 419
Danielle M. Gorbach United States 9 238 0.9× 56 0.5× 28 0.4× 65 0.9× 24 0.6× 9 330
F. C. Gunsett United States 12 309 1.1× 39 0.4× 85 1.2× 161 2.3× 187 4.7× 24 479
Trygve Solberg Norway 11 766 2.8× 22 0.2× 372 5.2× 102 1.5× 125 3.1× 16 849

Countries citing papers authored by André Garcia

Since Specialization
Citations

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

Fields of papers citing papers by André Garcia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of André Garcia

This figure shows the co-authorship network connecting the top 25 collaborators of André Garcia. A scholar is included among the top collaborators of André Garcia 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 André Garcia. André Garcia 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.
Garcia, André, et al.. (2025). Genetic Heterogeneity of Residual Variance for Foot Score Traits in American Angus Cattle. Journal of Animal Breeding and Genetics. 143(1). 68–78.
2.
Cesarani, Alberto, Andrea Criscione, Jorge Hidalgo, et al.. (2024). Effect of genotyping density on the detection of runs of homozygosity and heterozygosity in cattle. Journal of Animal Science. 102. 3 indexed citations
3.
Garcia, André, Matias Bermann, S. Tsuruta, et al.. (2024). Comparing algorithms to approximate accuracies for single-step genomic best linear unbiased predictor. Journal of Animal Science. 102.
4.
Emon, Megan L Van, et al.. (2023). Characterizing Foot and Leg Scores for Montana’s Registered Angus Cattle. Animals. 13(18). 2849–2849. 1 indexed citations
5.
Cesarani, Alberto, Jorge Hidalgo, André Garcia, et al.. (2023). Genetic background of semen parameters in Italian Simmental bulls. Italian Journal of Animal Science. 22(1). 76–83. 1 indexed citations
6.
Garcia, André, et al.. (2023). Across-country genetic and genomic analyses of foot score traits in American and Australian Angus cattle. Genetics Selection Evolution. 55(1). 76–76. 5 indexed citations
7.
8.
Garcia, André, Ignácio Aguilar, Andrés Legarra, et al.. (2022). Theoretical accuracy for indirect predictions based on SNP effects from single-step GBLUP. Genetics Selection Evolution. 54(1). 66–66. 7 indexed citations
9.
Hidalgo, Jorge, Daniela Lourenço, S. Tsuruta, et al.. (2021). Changes in genomic predictions when new information is added. Journal of Animal Science. 99(2). 7 indexed citations
10.
Knol, E.F., André Garcia, Marcos S. Lopes, et al.. (2021). Investigating pig survival in different production phases using genomic models. Journal of Animal Science. 99(8). 16 indexed citations
11.
Hidalgo, Jorge, et al.. (2021). Genetic Background and Inbreeding Depression in Romosinuano Cattle Breed in Mexico. Animals. 11(2). 321–321. 20 indexed citations
12.
Cesarani, Alberto, André Garcia, Jorge Hidalgo, et al.. (2021). Genomic information allows for more accurate breeding values for milkability in dual-purpose Italian Simmental cattle. Journal of Dairy Science. 104(5). 5719–5727. 18 indexed citations
13.
Al-Tobasei, Rafet, Ali Ali, André Garcia, et al.. (2021). Genomic predictions for fillet yield and firmness in rainbow trout using reduced-density SNP panels. BMC Genomics. 22(1). 92–92. 24 indexed citations
14.
Cesarani, Alberto, Jorge Hidalgo, André Garcia, et al.. (2020). Beef trait genetic parameters based on old and recent data and its implications for genomic predictions in Italian Simmental cattle. Journal of Animal Science. 98(8). 21 indexed citations
15.
Bosworth, Brian G., Geoff Waldbieser, André Garcia, & Daniela Lourenço. (2019). Effect of pond‐ or strip‐spawning on growth and carcass yield of channel catfish progeny, Ictalurus punctatus. Journal of the World Aquaculture Society. 51(2). 407–417. 1 indexed citations
16.
Roça, Roberto de Oliveira, et al.. (2019). Challenge with fumonisin FB1 + FB2 alters profile of fatty acids in Nile tilapia fingerlings. Aquaculture. 516. 734546–734546. 4 indexed citations
17.
Garcia, André, et al.. (2019). Zebrafish breeding program: genetic parameters estimates for growth traits. Journal of Applied Genetics. 60(2). 209–216. 2 indexed citations
18.
Garcia, André, Brian G. Bosworth, Geoffrey C. Waldbieser, et al.. (2018). Development of genomic predictions for harvest and carcass weight in channel catfish. Genetics Selection Evolution. 50(1). 66–66. 66 indexed citations
19.
Garcia, André, et al.. (2017). Genetic parameters for growth performance, fillet traits, and fat percentage of male Nile tilapia (Oreochromis niloticus). Journal of Applied Genetics. 58(4). 527–533. 22 indexed citations
20.
Gasparino, Eliane, et al.. (2013). Effect of glycerol on GHR and IGF-1 gene expression in breast muscle and on growth of Japanese meat quails. Genetics and Molecular Research. 12(3). 3856–3861. 2 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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