E. Ugarte

1.3k total citations
45 papers, 990 citations indexed

About

E. Ugarte is a scholar working on Genetics, Agronomy and Crop Science and Animal Science and Zoology. According to data from OpenAlex, E. Ugarte has authored 45 papers receiving a total of 990 indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Genetics, 24 papers in Agronomy and Crop Science and 8 papers in Animal Science and Zoology. Recurrent topics in E. Ugarte's work include Genetic and phenotypic traits in livestock (35 papers), Ruminant Nutrition and Digestive Physiology (11 papers) and Reproductive Physiology in Livestock (11 papers). E. Ugarte is often cited by papers focused on Genetic and phenotypic traits in livestock (35 papers), Ruminant Nutrition and Digestive Physiology (11 papers) and Reproductive Physiology in Livestock (11 papers). E. Ugarte collaborates with scholars based in Spain, France and Morocco. E. Ugarte's co-authors include Andrés Legarra, Óscar González-Recio, Evangelina López de Maturana, R. Alenda, À. Bach, M. J. Carabaño, I. Beltrán de Heredia, L. Varona, M. D. Pérez-Guzmán and Manuel Ramón and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

E. Ugarte

43 papers receiving 945 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
E. Ugarte Spain 20 707 540 268 120 90 45 990
A. Carta Italy 16 693 1.0× 403 0.7× 208 0.8× 117 1.0× 84 0.9× 65 1.1k
Robert L Weaber United States 19 793 1.1× 363 0.7× 491 1.8× 164 1.4× 146 1.6× 65 1.2k
A. A. do Egito Brazil 17 636 0.9× 214 0.4× 250 0.9× 74 0.6× 108 1.2× 64 882
A. K. Chakravarty India 16 520 0.7× 459 0.8× 333 1.2× 110 0.9× 79 0.9× 131 1.0k
N. J. Corbet Australia 17 856 1.2× 563 1.0× 320 1.2× 162 1.4× 71 0.8× 43 1.1k
Sara Casu Italy 16 448 0.6× 326 0.6× 145 0.5× 87 0.7× 53 0.6× 54 769
Pramod Kumar Rout India 19 628 0.9× 424 0.8× 367 1.4× 210 1.8× 81 0.9× 111 1.1k
Matthew L Spangler United States 16 667 0.9× 292 0.5× 215 0.8× 105 0.9× 126 1.4× 96 999
Birgit Fuerst‐Waltl Austria 22 975 1.4× 744 1.4× 487 1.8× 327 2.7× 109 1.2× 113 1.4k
Megan M Rolf United States 15 1.1k 1.6× 326 0.6× 280 1.0× 67 0.6× 233 2.6× 38 1.3k

Countries citing papers authored by E. Ugarte

Since Specialization
Citations

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

Fields of papers citing papers by E. Ugarte

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of E. Ugarte

This figure shows the co-authorship network connecting the top 25 collaborators of E. Ugarte. A scholar is included among the top collaborators of E. Ugarte 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 E. Ugarte. E. Ugarte 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.
Carabaño, M. J., Hélène Larroque, E. Ugarte, et al.. (2025). Climate resilience differs across dairy sheep populations in Europe. animal. 19(7). 101570–101570.
2.
Astruc, Jean‐Michel, et al.. (2022). High genetic correlation for milk yield across Manech and Latxa dairy sheep from France and Spain. SHILAP Revista de lepidopterología. 3(4). 260–264. 4 indexed citations
3.
Varona, L., et al.. (2021). Genotyping strategies for maximizing genomic information in evaluations of the Latxa dairy sheep breed. Journal of Dairy Science. 104(6). 6861–6872. 6 indexed citations
4.
Goiri, Idoia, Raquel Atxaerandio, A. García-Rodríguez, et al.. (2020). Mitigation of greenhouse gases in dairy cattle via genetic selection: 1. Genetic parameters of direct methane using noninvasive methods and proxies of methane. Journal of Dairy Science. 103(8). 7199–7209. 39 indexed citations
5.
Legarra, Andrés, et al.. (2020). Exploring the inclusion of genomic information and metafounders in Latxa dairy sheep genetic evaluations. Journal of Dairy Science. 103(7). 6346–6353. 15 indexed citations
6.
González-Recio, Óscar, et al.. (2020). Mitigation of greenhouse gases in dairy cattle via genetic selection: 2. Incorporating methane emissions into the breeding goal. Journal of Dairy Science. 103(8). 7210–7221. 64 indexed citations
7.
Rodríguez‐Ramilo, Silvia Teresa, et al.. (2020). Inbreeding, effective population size, and coancestry in the Latxa dairy sheep breed. Journal of Dairy Science. 103(6). 5215–5226. 14 indexed citations
8.
Juste, Ramón A., et al.. (2020). Milk production losses in Latxa dairy sheep associated with small ruminant lentivirus infection. Preventive Veterinary Medicine. 176. 104886–104886. 19 indexed citations
9.
Ramón, Manuel, et al.. (2019). Estimation of the Genetic Parameters for Semen Traits in Spanish Dairy Sheep. Animals. 9(12). 1147–1147. 8 indexed citations
10.
Menéndez‐Buxadera, A., M. J. Carabaño, Óscar González-Recio, et al.. (2013). Reaction norm of fertility traits adjusted for protein and fat production level across lactations in Holstein cattle. Journal of Dairy Science. 96(7). 4653–4665. 9 indexed citations
11.
Vitezica, Zulma G., I. Beltrán de Heredia, & E. Ugarte. (2013). Short communication: Analysis of association between the prion protein (PRNP) locus and milk traits in Latxa dairy sheep. Journal of Dairy Science. 96(9). 6079–6083. 7 indexed citations
12.
David, Ingrid, M. J. Carabaño, Llibertat Tusell, et al.. (2010). Product versus additive model for studying artificial insemination results in several livestock populations. Journal of Animal Science. 89(2). 321–328. 7 indexed citations
13.
Ramón, Manuel, Andrés Legarra, E. Ugarte, José Julián Garde, & M. D. Pérez-Guzmán. (2010). Economic weights for major milk constituents of Manchega dairy ewes. Journal of Dairy Science. 93(7). 3303–3309. 7 indexed citations
14.
Maturana, Evangelina López de, Andrés Legarra, L. Varona, & E. Ugarte. (2007). Analysis of Fertility and Dystocia in Holsteins Using Recursive Models to Handle Censored and Categorical Data. Journal of Dairy Science. 90(4). 2012–2024. 75 indexed citations
15.
Maturana, Evangelina López de, E. Ugarte, & Óscar González-Recio. (2007). Impact of Calving Ease on Functional Longevity and Herd Amortization Costs in Basque Holsteins Using Survival Analysis. Journal of Dairy Science. 90(9). 4451–4457. 43 indexed citations
16.
Legarra, Andrés, Manuel Ramón, E. Ugarte, & M. D. Pérez-Guzmán. (2007). Economic weights of fertility, prolificacy, milk yield and longevity in dairy sheep. animal. 1(2). 193–203. 41 indexed citations
17.
Serradilla, J.M. & E. Ugarte. (2006). Emerging genetic programs for small dairy ruminants.. 2–5. 3 indexed citations
18.
Ugarte, E., et al.. (1998). Genetic evaluation of calving ease in Spanish Holstein population. Bulletin - International Bull Evaluation Service/Interbull bulletin. 21. 9 indexed citations
19.
Ugarte, E., et al.. (1996). Genetic Parameters and Trends for Milk Production of Blond-Faced Latxa Sheep Using Bayesian Analysis. Journal of Dairy Science. 79(12). 2268–2277. 21 indexed citations
20.
Monplaisir, N, C. Neisson-Vernant, M Bouillot, et al.. (1993). HTLV-I Maternal Transmission in Martinique, Using Serology and Polymerase Chain Reaction. AIDS Research and Human Retroviruses. 9(9). 869–874. 20 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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