Mamen Oliván

1.6k total citations
55 papers, 1.2k citations indexed

About

Mamen Oliván is a scholar working on Animal Science and Zoology, Genetics and Molecular Biology. According to data from OpenAlex, Mamen Oliván has authored 55 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Animal Science and Zoology, 13 papers in Genetics and 11 papers in Molecular Biology. Recurrent topics in Mamen Oliván's work include Meat and Animal Product Quality (39 papers), Animal Nutrition and Physiology (14 papers) and Genetic and phenotypic traits in livestock (13 papers). Mamen Oliván is often cited by papers focused on Meat and Animal Product Quality (39 papers), Animal Nutrition and Physiology (14 papers) and Genetic and phenotypic traits in livestock (13 papers). Mamen Oliván collaborates with scholars based in Spain, Portugal and Ireland. Mamen Oliván's co-authors include K. Osoro, Verónica Sierra, L.M.M. Ferreira, R. Celaya, Ana Coto‐Montes, Noelia Aldai, Antonio Hernández Martínez, M.A.M. Rodrigues, U. García and Miguel Ángel Sentandreu and has published in prestigious journals such as Journal of Agricultural and Food Chemistry, Food Chemistry and Meat Science.

In The Last Decade

Mamen Oliván

55 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mamen Oliván Spain 22 678 377 337 171 125 55 1.2k
F. Peña Spain 19 646 1.0× 255 0.7× 354 1.1× 87 0.5× 91 0.7× 50 996
I. Sierra Spain 14 1.1k 1.6× 479 1.3× 488 1.4× 125 0.7× 109 0.9× 26 1.5k
Hervé Dubroeucq France 16 366 0.5× 318 0.8× 190 0.6× 116 0.7× 76 0.6× 27 755
Pedro Veiga Rodrigues Paulino Brazil 23 817 1.2× 1.1k 3.0× 695 2.1× 84 0.5× 181 1.4× 109 1.6k
T. R. Manley New Zealand 17 388 0.6× 780 2.1× 405 1.2× 174 1.0× 80 0.6× 29 1.4k
Elias Nunes Martins Brazil 18 690 1.0× 448 1.2× 337 1.0× 59 0.3× 98 0.8× 156 1.3k
Didier D. Micol France 25 2.1k 3.1× 895 2.4× 602 1.8× 422 2.5× 377 3.0× 76 2.7k
Hideaki Takahashi Japan 21 731 1.1× 120 0.3× 876 2.6× 354 2.1× 67 0.5× 89 1.9k
R. D. Wiedmeier United States 18 324 0.5× 763 2.0× 329 1.0× 83 0.5× 219 1.8× 46 1.1k
M.A. McNiven Canada 26 243 0.4× 337 0.9× 396 1.2× 182 1.1× 154 1.2× 66 1.8k

Countries citing papers authored by Mamen Oliván

Since Specialization
Citations

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

Fields of papers citing papers by Mamen Oliván

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mamen Oliván

This figure shows the co-authorship network connecting the top 25 collaborators of Mamen Oliván. A scholar is included among the top collaborators of Mamen Oliván 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 Mamen Oliván. Mamen Oliván 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.
Royo, L. J., Yolanda Diñeiro, S. García-Torres, et al.. (2024). Exploring the miRNAs Profile in Dark-Cutting Beef. Foods. 13(6). 960–960. 2 indexed citations
2.
3.
Sierra, Verónica, et al.. (2023). Role of the endoplasmic reticulum in the search for early biomarkers of meat quality. Meat Science. 203. 109224–109224. 6 indexed citations
4.
Garlito, Borja, Miguel Ángel Sentandreu, Vicent Yusà, et al.. (2022). New insights into the search of meat quality biomarkers assisted by Orbitrap Tribrid untargeted metabolite analysis and chemometrics. Food Chemistry. 407. 135173–135173. 7 indexed citations
5.
Aldai, Noelia, Enrique Sentandreu, Mamen Oliván, et al.. (2021). Caspase activity in post mortem muscle and its relation to cattle handling practices. Journal of the Science of Food and Agriculture. 101(15). 6258–6264. 6 indexed citations
6.
Sentandreu, Miguel Ángel, et al.. (2021). Proteomic pipeline for biomarker hunting of defective bovine meat assisted by liquid chromatography-mass spectrometry analysis and chemometrics. Journal of Proteomics. 238. 104153–104153. 14 indexed citations
7.
López‐Pedrouso, María, Laura Purriños, Mamen Oliván, et al.. (2020). Sensory and Physicochemical Analysis of Meat from Bovine Breeds in Different Livestock Production Systems, Pre-Slaughter Handling Conditions, and Ageing Time. Foods. 9(2). 176–176. 27 indexed citations
8.
Aldai, Noelia, Enrique Sentandreu, Mamen Oliván, et al.. (2018). Search for proteomic biomarkers related to bovine pre-slaughter stress using liquid isoelectric focusing (OFFGEL) and mass spectrometry. Journal of Proteomics. 198. 59–65. 29 indexed citations
9.
Oliván, Mamen, J. González, Anna Bassols, et al.. (2018). Effect of sex and RYR1 gene mutation on the muscle proteomic profile and main physiological biomarkers in pigs at slaughter. Meat Science. 141. 81–90. 18 indexed citations
10.
Potes, Yaiza, Juan Carlos Bermejo-Millo, María Fernández Fernández, et al.. (2018). Overweight in the Elderly Induces a Switch in Energy Metabolism that Undermines Muscle Integrity. Aging and Disease. 10(2). 217–217. 31 indexed citations
11.
Potes, Yaiza, Ignacio Vega‐Naredo, Verónica Sierra, et al.. (2015). Effect of animal mixing as a stressor on biomarkers of autophagy and oxidative stress during pig muscle maturation. animal. 9(7). 1188–1194. 20 indexed citations
12.
Hollung, Kristin, Anna Maria Timperio, Mamen Oliván, et al.. (2014). Systems Biology: A New Tool for Farm Animal Science. Current Protein and Peptide Science. 15(2). 100–117. 9 indexed citations
13.
Sierra, Verónica, K. Osoro, Ignacio Vega‐Naredo, et al.. (2012). Identification of biomarkers of meat tenderisation and its use for early classification of Asturian beef into fast and late tenderising meat. Journal of the Science of Food and Agriculture. 92(13). 2727–2740. 27 indexed citations
14.
Sierra, Verónica, et al.. (2007). Prediction of the fatty acid composition of beef by near infrared transmittance spectroscopy. Meat Science. 78(3). 248–255. 63 indexed citations
15.
Aldai, Noelia, Brendan E. Murray, Mamen Oliván, et al.. (2005). The influence of breed and mh-genotype on carcass conformation, meat physico-chemical characteristics, and the fatty acid profile of muscle from yearling bulls. Meat Science. 72(3). 486–495. 62 indexed citations
16.
Oliván, Mamen, Antonio Hernández Martínez, K. Osoro, et al.. (2004). Effect of muscular hypertrophy on physico-chemical, biochemical and texture traits of meat from yearling bulls. Meat Science. 68(4). 567–575. 42 indexed citations
17.
Ferreira, L.M.M., Mamen Oliván, M.A.M. Rodrigues, et al.. (2004). Estimation of feed intake by cattle using controlled-release capsules containing n-alkanes or chromium sesquioxide. The Journal of Agricultural Science. 142(2). 225–234. 33 indexed citations
18.
19.
Oliván, Mamen, et al.. (2001). Estimation of the carcass composition of yearling bulls of “Asturiana de los Valles” breed from the dissection of a rib joint. Meat Science. 57(2). 185–190. 23 indexed citations
20.
Oliván, Mamen, K. Osoro, & R. Celaya. (1995). Comportamiento y rendimiento de las vacas de cría manejadas en comunidades vegetales naturales de montaña.. 23–38. 4 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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