A. Rogberg‐Muñoz

778 total citations
47 papers, 501 citations indexed

About

A. Rogberg‐Muñoz is a scholar working on Genetics, Molecular Biology and Agronomy and Crop Science. According to data from OpenAlex, A. Rogberg‐Muñoz has authored 47 papers receiving a total of 501 indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Genetics, 14 papers in Molecular Biology and 14 papers in Agronomy and Crop Science. Recurrent topics in A. Rogberg‐Muñoz's work include Genetic and phenotypic traits in livestock (32 papers), Genetic Mapping and Diversity in Plants and Animals (17 papers) and Meat and Animal Product Quality (13 papers). A. Rogberg‐Muñoz is often cited by papers focused on Genetic and phenotypic traits in livestock (32 papers), Genetic Mapping and Diversity in Plants and Animals (17 papers) and Meat and Animal Product Quality (13 papers). A. Rogberg‐Muñoz collaborates with scholars based in Argentina, China and Colombia. A. Rogberg‐Muñoz's co-authors include Guillermo Giovambattista, Marìa Verònica Ripoli, Pilar Peral García, Daniel E. Goszczynski, Juan Pedro Lirón, Diego Manuel Posik, L. M. Melucci, E. L. Villarreal, C. A. Mezzadra and R. J. C. Cantet and has published in prestigious journals such as Free Radical Biology and Medicine, Journal of Dairy Science and Gene.

In The Last Decade

A. Rogberg‐Muñoz

42 papers receiving 475 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
A. Rogberg‐Muñoz Argentina 13 336 140 116 111 57 47 501
Mohammad Reza Nassiry Iran 12 303 0.9× 172 1.2× 104 0.9× 128 1.2× 50 0.9× 41 537
Marìa Verònica Ripoli Argentina 16 466 1.4× 135 1.0× 192 1.7× 179 1.6× 53 0.9× 49 684
A. Tomás Spain 13 379 1.1× 145 1.0× 88 0.8× 77 0.7× 65 1.1× 26 530
S. K. Niranjan India 14 391 1.2× 108 0.8× 80 0.7× 179 1.6× 101 1.8× 85 547
Brittney N. Keel United States 13 268 0.8× 113 0.8× 142 1.2× 73 0.7× 82 1.4× 46 471
Patrick Monametsi Kgwatalala Botswana 11 249 0.7× 138 1.0× 76 0.7× 133 1.2× 50 0.9× 31 440
Mervi Honkatukia Finland 12 350 1.0× 237 1.7× 103 0.9× 57 0.5× 63 1.1× 27 543
Hailu Dadi South Korea 16 590 1.8× 103 0.7× 92 0.8× 185 1.7× 132 2.3× 37 707
Lorraine Pariset Italy 20 562 1.7× 108 0.8× 220 1.9× 152 1.4× 97 1.7× 39 782
B. K. Joshi India 15 508 1.5× 119 0.8× 128 1.1× 293 2.6× 62 1.1× 70 718

Countries citing papers authored by A. Rogberg‐Muñoz

Since Specialization
Citations

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

Fields of papers citing papers by A. Rogberg‐Muñoz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by A. Rogberg‐Muñoz. 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 A. Rogberg‐Muñoz. The network helps show where A. Rogberg‐Muñoz may publish in the future.

Co-authorship network of co-authors of A. Rogberg‐Muñoz

This figure shows the co-authorship network connecting the top 25 collaborators of A. Rogberg‐Muñoz. A scholar is included among the top collaborators of A. Rogberg‐Muñoz 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 A. Rogberg‐Muñoz. A. Rogberg‐Muñoz 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.
García, Pilar Peral, et al.. (2025). Divergent adaptation to highland and tropical environments in Bolivian Creole cattle. Gene. 949. 149354–149354. 3 indexed citations
2.
Rogberg‐Muñoz, A., et al.. (2024). Genomic diversity study of highly crossbred cattle population in a Low and Middle Tropical environment. Tropical Animal Health and Production. 56(8). 258–258. 1 indexed citations
3.
Rogberg‐Muñoz, A., et al.. (2022). Genome‐wide scan for signatures of selection in the Brangus cattle genome. Journal of Animal Breeding and Genetics. 139(6). 679–694. 4 indexed citations
4.
Martini, Johannes W. R., E.C.G. Pimentel, Sebastián Munilla, et al.. (2018). The effect of the H−1 scaling factors τ and ω on the structure of H in the single-step procedure. Genetics Selection Evolution. 50(1). 16–16. 29 indexed citations
5.
Giovambattista, Guillermo, et al.. (2018). Computational prediction of nsSNPs effects on protein function and structure, a prioritization approach for further in vitro studies applied to bovine GSTP1. Free Radical Biology and Medicine. 129. 486–491. 2 indexed citations
6.
Cantet, R. J. C., et al.. (2017). Beyond genomic selection: The animal model strikes back (one generation)!. Journal of Animal Breeding and Genetics. 134(3). 224–231. 4 indexed citations
7.
Goszczynski, Daniel E., Hervé Durand, A. Rogberg‐Muñoz, et al.. (2017). Evidence of positive selection towards Zebuine haplotypes in the BoLA region of Brangus cattle. animal. 12(2). 215–223. 32 indexed citations
8.
9.
Goszczynski, Daniel E., Marìa Verònica Ripoli, E. L. Villarreal, et al.. (2016). Genetic characterisation of PPARG, CEBPA and RXRA, and their influence on meat quality traits in cattle. Journal of Animal Science and Technology. 58(1). 14–14. 15 indexed citations
10.
Rogberg‐Muñoz, A., Daniel E. Goszczynski, Juan Pedro Lirón, et al.. (2015). Study of the influence of genes related to muscle oxidative processes on beef color. Meat Science. 108. 17–20. 3 indexed citations
11.
Goszczynski, Daniel E., Marìa Verònica Ripoli, L. M. Melucci, et al.. (2015). Growth, carcass and meat quality traits in beef from Angus, Hereford and cross-breed grazing steers, and their association with SNPs in genes related to fat deposition metabolism. Meat Science. 114. 121–129. 40 indexed citations
12.
Rogberg‐Muñoz, A., Shouhui Wei, Marìa Verònica Ripoli, et al.. (2015). Effectiveness of a 95 SNP panel for the screening of breed label fraud in the Chinese meat market. Meat Science. 111. 47–52. 12 indexed citations
13.
Goszczynski, Daniel E., Marìa Verònica Ripoli, E. L. Villarreal, et al.. (2014). Characterization of the bovine gene LIPE and possible influence on fatty acid composition of meat. Meta Gene. 2. 746–760. 15 indexed citations
14.
Ripoli, Marìa Verònica, Shengjuan Wei, A. Rogberg‐Muñoz, et al.. (2013). Evaluation of six single nucleotide polymorphisms for bovine traceability in the context of the argentine-chinese beef trade. Americanae (AECID Library). 24(2). 31–45. 2 indexed citations
15.
Rogberg‐Muñoz, A., et al.. (2013). Recent Patents for Detecting the Species of Origin in Animal Feedstuff, and Raw and Processed Meat Products. Recent Patents on Food Nutrition & Agriculture. 5(1). 3–8. 7 indexed citations
16.
Melucci, L. M., E. L. Villarreal, G. Grigioni, et al.. (2012). Genetic and management factors affecting beef quality in grazing Hereford steers. Meat Science. 92(4). 768–774. 18 indexed citations
17.
Giovambattista, Guillermo, A. Rogberg‐Muñoz, Marìa Verònica Ripoli, et al.. (2010). La genética molecular de bovinos y equinos criollos en los albores del siglo XXI. Americanae (AECID Library). 21(2). 0–0. 1 indexed citations
18.
Lirón, Juan Pedro, Marìa Verònica Ripoli, A. Rogberg‐Muñoz, et al.. (2010). Characterization and validation of bovine Gonadotripin releasing hormone receptor (GNRHR) polymorphisms. Research in Veterinary Science. 91(3). 391–396. 14 indexed citations
19.
Rogberg‐Muñoz, A., et al.. (2008). Animal Markers Assisted Selection in South America: A Point of View. PubMed. 2(2). 133–139. 1 indexed citations
20.
Echeverría, María Gabriela, et al.. (2008). Development of an ELA‐DRA gene typing method based on pyrosequencing technology. Tissue Antigens. 72(5). 464–468. 6 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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