Ramona N. Pena

2.6k total citations
106 papers, 1.8k citations indexed

About

Ramona N. Pena is a scholar working on Genetics, Animal Science and Zoology and Molecular Biology. According to data from OpenAlex, Ramona N. Pena has authored 106 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 70 papers in Genetics, 66 papers in Animal Science and Zoology and 25 papers in Molecular Biology. Recurrent topics in Ramona N. Pena's work include Genetic and phenotypic traits in livestock (50 papers), Meat and Animal Product Quality (37 papers) and Genetic Mapping and Diversity in Plants and Animals (32 papers). Ramona N. Pena is often cited by papers focused on Genetic and phenotypic traits in livestock (50 papers), Meat and Animal Product Quality (37 papers) and Genetic Mapping and Diversity in Plants and Animals (32 papers). Ramona N. Pena collaborates with scholars based in Spain, United Kingdom and Italy. Ramona N. Pena's co-authors include J. Estany, M. Tör, Marcel Amills, Raquel Quintanilla, Roger Ros‐Freixedes, Ángela Cánovas, J. M. Folch, David Gallardo, Ana I. Fernández and Óscar Ramírez and has published in prestigious journals such as PLoS ONE, Scientific Reports and Biochemical and Biophysical Research Communications.

In The Last Decade

Ramona N. Pena

98 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ramona N. Pena Spain 24 1.0k 751 620 267 247 106 1.8k
M.F.W. te Pas Netherlands 29 1.1k 1.1× 914 1.2× 865 1.4× 279 1.0× 366 1.5× 104 2.5k
Raquel Quintanilla Spain 25 1.2k 1.2× 630 0.8× 408 0.7× 285 1.1× 182 0.7× 91 1.8k
Maiqing Zheng China 31 841 0.8× 1.2k 1.5× 945 1.5× 410 1.5× 359 1.5× 101 2.5k
Nick V. L. Serão United States 22 541 0.5× 585 0.8× 386 0.6× 153 0.6× 147 0.6× 96 1.5k
Carine Nezer Belgium 16 1.2k 1.1× 401 0.5× 685 1.1× 226 0.8× 75 0.3× 25 2.0k
Junwu Ma China 27 1.2k 1.2× 641 0.9× 498 0.8× 453 1.7× 160 0.6× 70 1.8k
Dajeong Lim South Korea 24 1.0k 1.0× 362 0.5× 405 0.7× 425 1.6× 87 0.4× 129 1.5k
Dewu Liu China 22 699 0.7× 244 0.3× 911 1.5× 334 1.3× 64 0.3× 117 1.7k
Chenglong Luo China 21 648 0.6× 605 0.8× 507 0.8× 128 0.5× 96 0.4× 64 1.4k
R. Davoli Italy 34 1.7k 1.6× 1.3k 1.8× 942 1.5× 409 1.5× 299 1.2× 144 3.0k

Countries citing papers authored by Ramona N. Pena

Since Specialization
Citations

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

Fields of papers citing papers by Ramona N. Pena

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ramona N. Pena. 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 Ramona N. Pena. The network helps show where Ramona N. Pena may publish in the future.

Co-authorship network of co-authors of Ramona N. Pena

This figure shows the co-authorship network connecting the top 25 collaborators of Ramona N. Pena. A scholar is included among the top collaborators of Ramona N. Pena 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 Ramona N. Pena. Ramona N. Pena 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.
Pena, Ramona N., et al.. (2025). Gut microbiota modulation and inflammation mitigation in a murine model through a hull-less and purple grain barley genotype. Food & Function. 16(6). 2389–2400. 1 indexed citations
2.
Santacreu, M. A., et al.. (2025). Gut microbiota variations over the lifespan and longevity in rabbit’s maternal lines. Scientific Reports. 15(1). 17874–17874.
3.
González-Rodríguez, Olga, Llilianne Ganges, Marta Díaz, et al.. (2024). Insights into genetic determinants of piglet survival during a PRRSV outbreak. Veterinary Research. 55(1). 160–160.
4.
Fraile, Lorenzo, et al.. (2024). Candidate markers for enhanced host response to PRRS have scarce adverse effects on pigs’ growth and production. Porcine Health Management. 10(1). 29–29. 2 indexed citations
5.
Laplana, Marina, et al.. (2024). Sequence variants associated with resilient responses in growing pigs. Journal of Animal Breeding and Genetics. 142(1). 79–91. 2 indexed citations
6.
Fraile, Lorenzo, et al.. (2024). Selection for Resilience in Livestock Production Systems. International Journal of Molecular Sciences. 25(23). 13109–13109. 2 indexed citations
7.
Pena, Ramona N., et al.. (2024). Association between mitochondrial DNA copy number and production traits in pigs. Journal of Animal Breeding and Genetics. 142(2). 170–183. 1 indexed citations
8.
Ros‐Freixedes, Roger, et al.. (2023). The leptin receptor gene affects piglet behavior and growth. Journal of Animal Science. 101. 1 indexed citations
9.
10.
Balcells, J., Ahmad Reza Seradj, Ramona N. Pena, et al.. (2022). Age Evolution of Lipid Accretion Rate in Boars Selected for Lean Meat and Duroc Barrows. Animals. 12(14). 1868–1868.
11.
Fraile, Lorenzo, et al.. (2022). A genome-wide screen for resilient responses in growing pigs. Genetics Selection Evolution. 54(1). 50–50. 4 indexed citations
12.
Tör, M., Roger Ros‐Freixedes, Javier Álvarez Rodríguez, et al.. (2021). Circulating Non-Esterified Fatty Acids as Biomarkers for Fat Content and Composition in Pigs. Animals. 11(2). 386–386. 9 indexed citations
13.
Noguera, José Luís, Ramona N. Pena, María Ballester, et al.. (2021). Comparative Transcriptome Profile between Iberian Pig Varieties Provides New Insights into Their Distinct Fat Deposition and Fatty Acids Content. Animals. 11(3). 627–627. 10 indexed citations
14.
Pena, Ramona N., Roger Ros‐Freixedes, J. Reixach, et al.. (2021). A Methodology to Quantify Resilience in Growing Pigs. Animals. 11(10). 2970–2970. 13 indexed citations
15.
Ros‐Freixedes, Roger, et al.. (2014). Genome-Wide Association Study for Intramuscular Fat Content and Composition in Duroc Pigs. Proceedings of the World Congress on Genetics Applied to Livestock Production. 929. 1 indexed citations
16.
Estany, J., Roger Ros‐Freixedes, M. Tör, & Ramona N. Pena. (2014). A Functional Variant in the Stearoyl-CoA Desaturase Gene Promoter Enhances Fatty Acid Desaturation in Pork. PLoS ONE. 9(1). e86177–e86177. 52 indexed citations
17.
Manunza, Arianna, J. Casellas, Raquel Quintanilla, et al.. (2014). A genome-wide association analysis for porcine serum lipid traits reveals the existence of age-specific genetic determinants. BMC Genomics. 15(1). 758–758. 24 indexed citations
18.
Ros‐Freixedes, Roger, Ramona N. Pena, Mahmut Tör, & J. Estany. (2013). Breeding for high oleic acid content in pork using direct selection and molecular markers.. 580–582.
19.
Ros‐Freixedes, Roger, et al.. (2013). Desaturase and elongase activity across tissues and genotypes in Duroc pigs.. 517–519.
20.
Pérez-Montarelo, Dafne, Ana I. Fernández, Ana I. Fernández, et al.. (2012). Joint effects of porcine leptin and leptin receptor polymorphisms on productivity and quality traits. Animal Genetics. 43(6). 805–809. 26 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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