I. Cervantes

2.3k total citations
78 papers, 1.6k citations indexed

About

I. Cervantes is a scholar working on Genetics, Animal Science and Zoology and Equine. According to data from OpenAlex, I. Cervantes has authored 78 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 66 papers in Genetics, 24 papers in Animal Science and Zoology and 16 papers in Equine. Recurrent topics in I. Cervantes's work include Genetic and phenotypic traits in livestock (64 papers), Genetic Mapping and Diversity in Plants and Animals (22 papers) and Veterinary Equine Medical Research (16 papers). I. Cervantes is often cited by papers focused on Genetic and phenotypic traits in livestock (64 papers), Genetic Mapping and Diversity in Plants and Animals (22 papers) and Veterinary Equine Medical Research (16 papers). I. Cervantes collaborates with scholars based in Spain, Peru and Vietnam. I. Cervantes's co-authors include Juan Pablo Gutiérrez, F. Goyache, M. Valera, A. Molina, Ester Bartolomé, María Sánchez, María Ángeles Pérez-Cabal, Noelia Ibáñez‐Escriche, A. L. Schaefer and I. Fernández and has published in prestigious journals such as Journal of Dairy Science, Journal of Animal Science and Heredity.

In The Last Decade

I. Cervantes

74 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
I. Cervantes Spain 21 1.3k 471 365 300 165 78 1.6k
M. Valera Spain 25 1.6k 1.2× 849 1.8× 491 1.3× 960 3.2× 238 1.4× 159 2.5k
A. Molina Spain 29 2.0k 1.6× 991 2.1× 645 1.8× 766 2.6× 286 1.7× 173 2.9k
H. Hamann Germany 26 994 0.8× 562 1.2× 460 1.3× 481 1.6× 518 3.1× 126 2.3k
Javier Cañón Spain 23 1.6k 1.2× 354 0.8× 315 0.9× 60 0.2× 105 0.6× 98 2.0k
I. Fernández Spain 26 1.5k 1.2× 285 0.6× 422 1.2× 46 0.2× 105 0.6× 95 1.9k
Juan Pablo Gutiérrez Spain 35 3.6k 2.7× 911 1.9× 1.1k 2.9× 396 1.3× 272 1.6× 159 4.2k
Samuel Rezende Paiva Brazil 30 2.3k 1.8× 1.1k 2.4× 719 2.0× 47 0.2× 298 1.8× 146 3.4k
Monika Reißmann Germany 21 948 0.7× 230 0.5× 136 0.4× 149 0.5× 39 0.2× 65 1.6k
R. L. Willham United States 20 1.5k 1.1× 613 1.3× 625 1.7× 177 0.6× 316 1.9× 80 2.0k
Dominik Burger Switzerland 19 512 0.4× 174 0.4× 397 1.1× 603 2.0× 160 1.0× 101 1.6k

Countries citing papers authored by I. Cervantes

Since Specialization
Citations

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

Fields of papers citing papers by I. Cervantes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of I. Cervantes

This figure shows the co-authorship network connecting the top 25 collaborators of I. Cervantes. A scholar is included among the top collaborators of I. Cervantes 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 I. Cervantes. I. Cervantes 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.
2.
Cervantes, I., et al.. (2024). Pedigree analysis in the mhorr gazelle (Nanger dama mhorr): Genetic variability evolution of the captive population. Ecology and Evolution. 14(2). e10876–e10876. 2 indexed citations
3.
Arias‐Álvarez, M., et al.. (2023). Embryo survival and fertility differ in lines divergently selected for birth weight homogeneity in mice. Journal of Animal Breeding and Genetics. 140(5). 549–557. 4 indexed citations
4.
Gutiérrez, Juan Pablo, et al.. (2023). Genetic parameters for fleece uniformity in alpacas. Journal of Animal Science. 101. 1 indexed citations
5.
Demyda‐Peyrás, S., et al.. (2022). Fine-tuning genomic and pedigree inbreeding rates in equine population with a deep and reliable stud book: the case of the Pura Raza Española horse. Journal of Animal Science and Biotechnology. 13(1). 127–127. 9 indexed citations
6.
Sánchez, María, et al.. (2021). Genetic parameters for canalization analysis of morphological traits in the Pura Raza Español horse. Journal of Animal Breeding and Genetics. 138(4). 482–490. 7 indexed citations
7.
Cervantes, I., et al.. (2019). Effect of feed restriction on the environmental variability of birth weight in divergently selected lines of mice. Genetics Selection Evolution. 51(1). 27–27. 10 indexed citations
8.
Varona, L., et al.. (2017). Cross-validation analysis for genetic evaluation models for ranking in endurance horses. animal. 12(1). 20–27. 12 indexed citations
9.
10.
Cervantes, I., Juan Pablo Gutiérrez, & T.H.E. Meuwissen. (2016). Response to selection while maximizing genetic variance in small populations. Genetics Selection Evolution. 48(1). 69–69. 20 indexed citations
11.
Gutiérrez, Juan Pablo, et al.. (2014). Weighting fibre and morphological traits in a genetic index for an alpaca breeding programme. animal. 8(3). 360–369. 22 indexed citations
12.
Cervantes, I. & T.H.E. Meuwissen. (2011). Maximization of total genetic variance in breed conservation programmes. Journal of Animal Breeding and Genetics. 128(6). 465–472. 8 indexed citations
13.
Gutiérrez, Juan Pablo, et al.. (2011). Genetic parameters for growth of fiber diameter in alpacas1. Journal of Animal Science. 89(8). 2310–2315. 21 indexed citations
14.
Bartolomé, Ester, F. Goyache, A. Molina, et al.. (2010). Pedigree estimation of the (sub) population contribution to the total gene diversity: the horse coat colour case. animal. 4(6). 867–875. 16 indexed citations
15.
Cervantes, I., Juan Pablo Gutiérrez, I. Fernández, & F. Goyache. (2009). Genetic relationships among calving ease, gestation length, and calf survival to weaning in the Asturiana de los Valles beef cattle breed1. Journal of Animal Science. 88(1). 96–101. 40 indexed citations
16.
Nagy, István, Ino Čurik, I. Radnai, et al.. (2009). Genetic diversity and population structure of the synthetic Pannon White rabbit revealed by pedigree analyses1. Journal of Animal Science. 88(4). 1267–1275. 28 indexed citations
17.
Cervantes, I., F. Goyache, & Juan Pablo Gutiérrez. (2008). El cociente entre incrementos de endogamia y de coascendencia como medida de subdivisión poblacional. Resultados preliminares. citaREA (Centro de Investigación y Tecnología Agroalimentaria de Aragón). 303–307.
18.
Azor, P. J., et al.. (2008). Análisis preliminar de la estructura genética del Merino: situación de las estirpes tradicionales mediante análisis genealógico y molecular. LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas). 295–302. 1 indexed citations
19.
Cervantes, I., F. Goyache, A. Molina, M. Valera, & Juan Pablo Gutiérrez. (2008). Application of individual increase in inbreeding to estimate realized effective sizes from real pedigrees. Journal of Animal Breeding and Genetics. 125(5). 301–310. 95 indexed citations
20.
Molleda, J. M., et al.. (2008). Fluorangiographic study of the ocular fundus in normal horses. Veterinary Ophthalmology. 11(s1). 2–7. 10 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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