Aroa Suárez‐Vega

1.4k total citations
57 papers, 812 citations indexed

About

Aroa Suárez‐Vega is a scholar working on Genetics, Cancer Research and Molecular Biology. According to data from OpenAlex, Aroa Suárez‐Vega has authored 57 papers receiving a total of 812 indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Genetics, 23 papers in Cancer Research and 15 papers in Molecular Biology. Recurrent topics in Aroa Suárez‐Vega's work include Genetic and phenotypic traits in livestock (38 papers), Cancer-related molecular mechanisms research (23 papers) and Genetic Mapping and Diversity in Plants and Animals (21 papers). Aroa Suárez‐Vega is often cited by papers focused on Genetic and phenotypic traits in livestock (38 papers), Cancer-related molecular mechanisms research (23 papers) and Genetic Mapping and Diversity in Plants and Animals (21 papers). Aroa Suárez‐Vega collaborates with scholars based in Spain, Canada and Australia. Aroa Suárez‐Vega's co-authors include Beatriz Gutiérrez‐Gil, Pablo Augusto de Souza Fonseca, J. J. Arranz, Ángela Cánovas, Gabriele Marras, Gwenola Tosser‐Klopp, Christophe Klopp, F. Miglior, Juan-José Arranz and Pilar Frutos and has published in prestigious journals such as PLoS ONE, Scientific Reports and Journal of Dairy Science.

In The Last Decade

Aroa Suárez‐Vega

56 papers receiving 806 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Aroa Suárez‐Vega Spain 17 607 273 231 159 113 57 812
Gregório Miguel Ferreira de Camargo Brazil 19 1.0k 1.7× 254 0.9× 436 1.9× 129 0.8× 252 2.2× 91 1.2k
Pâmela A. Alexandre Australia 16 482 0.8× 187 0.7× 152 0.7× 263 1.7× 133 1.2× 61 785
Yongfu La China 15 421 0.7× 223 0.8× 244 1.1× 254 1.6× 130 1.2× 63 745
Marco Milanesi Italy 17 438 0.7× 155 0.6× 121 0.5× 152 1.0× 109 1.0× 37 644
Binyun Cao China 19 414 0.7× 277 1.0× 169 0.7× 393 2.5× 73 0.6× 58 871
Mohammed Abo-Ismail Canada 13 500 0.8× 126 0.5× 305 1.3× 86 0.5× 192 1.7× 33 698
Christèle Robert-Granié France 15 455 0.7× 83 0.3× 245 1.1× 102 0.6× 104 0.9× 28 638
Tingxian Deng China 12 329 0.5× 128 0.5× 154 0.7× 156 1.0× 117 1.0× 46 537
Kaixing Qu China 15 532 0.9× 218 0.8× 125 0.5× 224 1.4× 173 1.5× 67 729
Hailu Dadi South Korea 16 590 1.0× 132 0.5× 185 0.8× 92 0.6× 103 0.9× 37 707

Countries citing papers authored by Aroa Suárez‐Vega

Since Specialization
Citations

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

Fields of papers citing papers by Aroa Suárez‐Vega

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Aroa Suárez‐Vega. 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 Aroa Suárez‐Vega. The network helps show where Aroa Suárez‐Vega may publish in the future.

Co-authorship network of co-authors of Aroa Suárez‐Vega

This figure shows the co-authorship network connecting the top 25 collaborators of Aroa Suárez‐Vega. A scholar is included among the top collaborators of Aroa Suárez‐Vega 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 Aroa Suárez‐Vega. Aroa Suárez‐Vega 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.
Arranz, J. J., Aroa Suárez‐Vega, Beatriz Gutiérrez‐Gil, et al.. (2024). Assessment of milk metabolites as biomarkers for predicting feed efficiency in dairy sheep. Journal of Dairy Science. 107(7). 4743–4757. 7 indexed citations
2.
Gutiérrez‐Gil, Beatriz, et al.. (2024). Unraveling dynamic transcriptomic changes in sheep's lactating mammary gland following Escherichia coli lipopolysaccharide exposure. Journal of Dairy Science. 107(12). 11269–11282. 1 indexed citations
3.
Fonseca, Pablo Augusto de Souza, Aroa Suárez‐Vega, J. J. Arranz, & Beatriz Gutiérrez‐Gil. (2024). Integration of selective sweeps across the sheep genome: understanding the relationship between production and adaptation traits. Genetics Selection Evolution. 56(1). 40–40. 6 indexed citations
4.
Mateo, Javier, et al.. (2023). Relationships between growth-related traits with carcass and meat quality traits in Spanish Assaf suckling lambs. Livestock Science. 269. 105173–105173. 2 indexed citations
5.
Gutiérrez‐Gil, Beatriz, et al.. (2022). Low-density SNP panel for efficient imputation and genomic selection of milk production and technological traits in dairy sheep. Journal of Dairy Science. 105(10). 8199–8217. 7 indexed citations
6.
Suárez‐Vega, Aroa, et al.. (2021). Accuracy of Imputation of Microsatellite Markers from a 50K SNP Chip in Spanish Assaf Sheep. Animals. 11(1). 86–86. 8 indexed citations
7.
Suárez‐Vega, Aroa, et al.. (2021). Study on the concordance between different SNP‐genotyping platforms in sheep. Animal Genetics. 52(6). 868–880. 4 indexed citations
8.
Suárez‐Vega, Aroa, et al.. (2021). Genome-wide association studies (GWAS) and post-GWAS analyses for technological traits in Assaf and Churra dairy breeds. Journal of Dairy Science. 104(11). 11850–11866. 15 indexed citations
9.
Fonseca, Pablo Augusto de Souza, Aroa Suárez‐Vega, Gabriele Marras, & Ángela Cánovas. (2020). GALLO: An R package for genomic annotation and integration of multiple data sources in livestock for positional candidate loci. GigaScience. 9(12). 153 indexed citations
10.
Reverter, Antônio, Beatriz Gutiérrez‐Gil, Pâmela A. Alexandre, et al.. (2020). Gene Networks Driving Genetic Variation in Milk and Cheese-Making Traits of Spanish Assaf Sheep. Genes. 11(7). 715–715. 16 indexed citations
11.
Reverter, Antônio, et al.. (2020). A multiple-phenotype imputation procedure as a method for prediction of cheese-making efficiency in Spanish Assaf sheep. Journal of Animal Science. 98(12). 1 indexed citations
12.
13.
Lam, Stephanie, F. Miglior, Pablo Augusto de Souza Fonseca, et al.. (2020). Identification of functional candidate variants and genes for feed efficiency in Holstein and Jersey cattle breeds using RNA-sequencing. Journal of Dairy Science. 104(2). 1928–1950. 21 indexed citations
14.
Gutiérrez‐Gil, Beatriz, et al.. (2020). The Milk Microbiota of the Spanish Churra Sheep Breed: New Insights into the Complexity of the Milk Microbiome of Dairy Species. Animals. 10(9). 1463–1463. 16 indexed citations
15.
16.
Miglior, F., Aroa Suárez‐Vega, Pablo Augusto de Souza Fonseca, et al.. (2019). Genetic mechanisms regulating the host response during mastitis. Journal of Dairy Science. 102(10). 9043–9059. 33 indexed citations
17.
Suárez‐Vega, Aroa, Beatriz Gutiérrez‐Gil, Pablo G. Toral, et al.. (2019). Conjugated linoleic acid (CLA)-induced milk fat depression: application of RNA-Seq technology to elucidate mammary gene regulation in dairy ewes. Scientific Reports. 9(1). 12 indexed citations
18.
Suárez‐Vega, Aroa, J. J. Arranz, Valentín Pérez Pérez, et al.. (2018). Early adipose deposits in sheep: comparative analysis of the perirenal fat transcriptome of Assaf and Churra suckling lambs. Animal Genetics. 49(6). 605–617. 14 indexed citations
19.
20.
Benavides, Júlio, Aroa Suárez‐Vega, M. Fuertes, et al.. (2015). Generalized severe junctional epidermolysis bullosa with congenital absence of skin in churra lambs. Veterinary Dermatology. 26(5). 367–367. 1 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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