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1
Semi-parametric estimates of population accuracy and bias of predictions of breeding values and future phenotypes using the LR method
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Semi-parametric estimates of population accuracy and bias of predictions of breeding values and future phenotypes using the LR method

Legarra, Andres ; Reverter, Antonio

Genetics selection evolution (Paris), 2018-11-06, Vol.50 (1), p.53-53 [Periódico revisado por pares]

France: BioMed Central Ltd

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Correction to: Semi-parametric estimates of population accuracy and bias of predictions of breeding values and future phenotypes using the LR method
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Correction to: Semi-parametric estimates of population accuracy and bias of predictions of breeding values and future phenotypes using the LR method

Legarra, Andres ; Reverter, Antonio

Genetics selection evolution (Paris), 2019-11-22, Vol.51 (1), p.69-69 [Periódico revisado por pares]

London: BioMed Central Ltd

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3
Beyond differential expression: the quest for causal mutations and effector molecules
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Artigo
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Beyond differential expression: the quest for causal mutations and effector molecules

Hudson, Nicholas J ; Dalrymple, Brian P ; Reverter, Antonio

BMC genomics, 2012-07-31, Vol.13 (1), p.356-356 [Periódico revisado por pares]

England: BioMed Central Ltd

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4
The extent of linkage disequilibrium in beef cattle breeds using high-density SNP genotypes
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The extent of linkage disequilibrium in beef cattle breeds using high-density SNP genotypes

Porto-Neto, Laercio R ; Kijas, James W ; Reverter, Antonio

Genetics selection evolution (Paris), 2014-03-24, Vol.46 (1), p.22-22 [Periódico revisado por pares]

France: BioMed Central Ltd

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5
Combining partial correlation and an information theory approach to the reversed engineering of gene co-expression networks
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Combining partial correlation and an information theory approach to the reversed engineering of gene co-expression networks

Reverter, Antonio ; Chan, Eva K. F

Bioinformatics, 2008-11-01, Vol.24 (21), p.2491-2497 [Periódico revisado por pares]

Oxford: Oxford University Press

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6
Genomic Prediction of Breeding Values Using a Subset of SNPs Identified by Three Machine Learning Methods
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Genomic Prediction of Breeding Values Using a Subset of SNPs Identified by Three Machine Learning Methods

Li, Bo ; Zhang, Nanxi ; Wang, You-Gan ; George, Andrew W ; Reverter, Antonio ; Li, Yutao

Frontiers in genetics, 2018, Vol.9, p.237-237 [Periódico revisado por pares]

Switzerland: Frontiers Research Foundation

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7
Dominance and epistatic genetic variances for litter size in pigs using genomic models
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Dominance and epistatic genetic variances for litter size in pigs using genomic models

Vitezica, Zulma G ; Reverter, Antonio ; Herring, William ; Legarra, Andres

Genetics selection evolution (Paris), 2018-12-22, Vol.50 (1), p.71-71 [Periódico revisado por pares]

France: BioMed Central Ltd

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8
ImmuneDEX: a strategy for the genetic improvement of immune competence in Australian Angus cattle
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ImmuneDEX: a strategy for the genetic improvement of immune competence in Australian Angus cattle

Reverter, Antonio ; Hine, Brad C ; Porto-Neto, Laercio ; Li, Yutao ; Duff, Christian J ; Dominik, Sonja ; Ingham, Aaron B

Journal of animal science, 2021-03-01, Vol.99 (3), p.1-7 [Periódico revisado por pares]

United States: Oxford University Press

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9
In silico validation of pooled genotyping strategies for genomic evaluation in Angus cattle
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In silico validation of pooled genotyping strategies for genomic evaluation in Angus cattle

Alexandre, Pâmela A ; Reverter, Antonio ; Lehnert, Sigrid A ; Porto-Neto, Laercio R ; Dominik, Sonja

Journal of animal science, 2020-06-01, Vol.98 (6), p.1-5 [Periódico revisado por pares]

United States: Oxford University Press

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10
Porcine tissue-specific regulatory networks derived from meta-analysis of the transcriptome
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Porcine tissue-specific regulatory networks derived from meta-analysis of the transcriptome

Pérez-Montarelo, Dafne ; Hudson, Nicholas J ; Fernández, Ana I ; Ramayo-Caldas, Yuliaxis ; Dalrymple, Brian P ; Reverter, Antonio de la Fuente, Alberto

PloS one, 2012, Vol.7 (9), p.e46159-e46159

United States: Public Library of Science

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