Hugo Naya

4.2k total citations · 1 hit paper
98 papers, 2.8k citations indexed

About

Hugo Naya is a scholar working on Molecular Biology, Genetics and Agronomy and Crop Science. According to data from OpenAlex, Hugo Naya has authored 98 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 48 papers in Molecular Biology, 34 papers in Genetics and 14 papers in Agronomy and Crop Science. Recurrent topics in Hugo Naya's work include Genetic and phenotypic traits in livestock (21 papers), Genomics and Phylogenetic Studies (19 papers) and RNA and protein synthesis mechanisms (14 papers). Hugo Naya is often cited by papers focused on Genetic and phenotypic traits in livestock (21 papers), Genomics and Phylogenetic Studies (19 papers) and RNA and protein synthesis mechanisms (14 papers). Hugo Naya collaborates with scholars based in Uruguay, United States and Brazil. Hugo Naya's co-authors include Daniel Gianola, Héctor Musto, Alejandro Zavala, Héctor Romero, K.A. Weigel, Gustavo de los Campos, Lucía Spangenberg, Andrés Legarra, José Miguel Cotes Torres and José Crossa and has published in prestigious journals such as SHILAP Revista de lepidopterología, Bioinformatics and PLoS ONE.

In The Last Decade

Hugo Naya

93 papers receiving 2.8k citations

Hit Papers

Predicting Quantitative Traits With Regression Models for... 2009 2026 2014 2020 2009 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hugo Naya Uruguay 26 1.3k 1.0k 593 398 378 98 2.8k
Rémy Bruggmann Switzerland 37 1.6k 1.3× 799 0.8× 816 1.4× 246 0.6× 276 0.7× 116 3.9k
Ted Sharpe United States 7 1.3k 1.1× 954 0.9× 663 1.1× 333 0.8× 216 0.6× 8 2.4k
Liliana Florea United States 28 2.3k 1.8× 972 0.9× 535 0.9× 299 0.8× 469 1.2× 68 4.0k
Konstantin Okonechnikov Germany 10 2.1k 1.7× 823 0.8× 829 1.4× 641 1.6× 302 0.8× 30 4.2k
Fernando García-Alcalde Spain 13 2.1k 1.6× 686 0.7× 682 1.2× 350 0.9× 556 1.5× 24 3.8k
Keren Byrne Australia 37 1.1k 0.8× 1.6k 1.5× 479 0.8× 455 1.1× 212 0.6× 82 3.5k
Geraldine Van Der Auwera Belgium 14 2.5k 2.0× 1.9k 1.9× 703 1.2× 509 1.3× 617 1.6× 18 4.9k
Mary J. O’Connell United States 27 1.4k 1.1× 563 0.5× 430 0.7× 339 0.9× 187 0.5× 99 2.7k
Stinus Lindgreen Denmark 14 1.8k 1.4× 928 0.9× 505 0.9× 787 2.0× 179 0.5× 18 3.1k
Daniel J. Turner United Kingdom 16 2.2k 1.8× 1.2k 1.2× 557 0.9× 475 1.2× 392 1.0× 22 3.3k

Countries citing papers authored by Hugo Naya

Since Specialization
Citations

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

Fields of papers citing papers by Hugo Naya

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hugo Naya

This figure shows the co-authorship network connecting the top 25 collaborators of Hugo Naya. A scholar is included among the top collaborators of Hugo Naya 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 Hugo Naya. Hugo Naya 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.
Raggio, Víctor, et al.. (2025). A labeled medical records corpus for the timely detection of rare diseases using machine learning approaches. Scientific Reports. 15(1). 6932–6932. 1 indexed citations
2.
Chilibroste, P., A. Meikle, María de Lourdes Adrien, et al.. (2025). Phytochemicals and Monensin in Dairy Cows: Impact on Productive Performance and Ruminal Fermentation Profile. Animals. 15(15). 2172–2172.
3.
Naya, Hugo, et al.. (2024). Energy efficiency of grazing Hereford heifers classified by paternal residual feed intake. Translational Animal Science. 8. txae005–txae005. 2 indexed citations
4.
Naya, Hugo, et al.. (2023). Energy efficiency, reproductive performance, and metabolic parameters of grazing Hereford heifers. Livestock Science. 279. 105389–105389. 1 indexed citations
5.
Greif, Gonzalo, et al.. (2022). Filogeografía de mitogenomas indígenas de Uruguay. Revista Argentina de Antropología Biológica. 24(1). 42–42. 3 indexed citations
6.
Nali, Luiz Henrique da Silva, Francielle Tramontini Gomes de Sousa, Ana Carolina Soares de Oliveira, et al.. (2020). Whole transcriptome analysis of multiple Sclerosis patients reveals active inflammatory profile in relapsing patients and downregulation of neurological repair pathways in secondary progressive cases. Multiple Sclerosis and Related Disorders. 44. 102243–102243. 12 indexed citations
7.
Fernández-Calero, Tamara, Cora Chalar, Helena Persson, et al.. (2020). Fine-tuning the metabolic rewiring and adaptation of translational machinery during an epithelial-mesenchymal transition in breast cancer cells. SHILAP Revista de lepidopterología. 8(1). 8–8. 6 indexed citations
8.
Pereira, Isabela Tiemy, Lucía Spangenberg, Anny Waloski Robert, et al.. (2018). Polysome profiling followed by RNA-seq of cardiac differentiation stages in hESCs. Scientific Data. 5(1). 180287–180287. 17 indexed citations
9.
Dallagiovanna, Bruno, et al.. (2017). lncRNAs are associated with polysomes during adipose-derived stem cell differentiation. Gene. 610. 103–111. 12 indexed citations
10.
Bozinovic, Francisco, Francisco Ferri‐Yáñez, Hugo Naya, Miguel B. Araújo, & Daniel E. Naya. (2014). Thermal tolerances in rodents: species that evolved in cold climates exhibit a wider thermoneutral zone. Evolutionary ecology research. 16(2). 143–152. 19 indexed citations
11.
Spangenberg, Lucía, Marco Augusto Stimamiglio, Patrícia Shigunov, et al.. (2014). Polysome Profiling Shows the Identity of Human Adipose-Derived Stromal/Stem Cells in Detail and Clearly Distinguishes Them from Dermal Fibroblasts. Stem Cells and Development. 23(22). 2791–2802. 10 indexed citations
12.
Naya, Daniel E., Lucía Spangenberg, Hugo Naya, & Francisco Bozinovic. (2013). Thermal conductance and basal metabolic rate are part of a coordinated system for heat transfer regulation. Proceedings of the Royal Society B Biological Sciences. 280(1767). 20131629–20131629. 22 indexed citations
13.
Naya, Daniel E., Lucía Spangenberg, Hugo Naya, & Francisco Bozinovic. (2012). HOW DOES EVOLUTIONARY VARIATION IN BASAL METABOLIC RATES ARISE? A STATISTICAL ASSESSMENT AND A MECHANISTIC MODEL. Evolution. 67(5). no–no. 35 indexed citations
14.
Peñagaricano, Francisco, et al.. (2012). Using high resolution melting analysis to identify variation of NPY, LEP and IGF-1 genes in Angus cattle. Livestock Science. 146(2-3). 193–198. 3 indexed citations
15.
Persson, Helena, Anders Kvist, Natalia Rego, et al.. (2011). Identification of New MicroRNAs in Paired Normal and Tumor Breast Tissue Suggests a Dual Role for the ERBB2/Her2 Gene. Cancer Research. 71(1). 78–86. 158 indexed citations
16.
Peñagaricano, Francisco, J. I. Urioste, Hugo Naya, G. de los Campos, & Daniel Gianola. (2010). Assessment of Poisson, Probit and linear models for genetic analysis of presence and number of black spots in Corriedale sheep. Journal of Animal Breeding and Genetics. 128(2). 105–113. 14 indexed citations
17.
Weigel, K.A., G. de los Campos, Óscar González-Recio, et al.. (2009). Predictive ability of direct genomic values for lifetime net merit of Holstein sires using selected subsets of single nucleotide polymorphism markers. Journal of Dairy Science. 92(10). 5248–5257. 98 indexed citations
18.
Naya, Hugo, Daniel Gianola, Héctor Romero, J. I. Urioste, & Héctor Musto. (2005). Inferring Parameters Shaping Amino Acid Usage in Prokaryotic Genomes via Bayesian MCMC Methods. Molecular Biology and Evolution. 23(1). 203–211. 16 indexed citations
19.
Zavala, Alejandro, et al.. (2005). Genomic GC content prediction in prokaryotes from a sample of genes. Gene. 357(2). 137–143. 11 indexed citations
20.
Musto, Héctor, Hugo Naya, Alejandro Zavala, et al.. (2004). Correlations between genomic GC levels and optimal growth temperatures in prokaryotes. FEBS Letters. 573(1-3). 73–77. 99 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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