about
Genome-wide association mapping including phenotypes from relatives without genotypes in a single-step (ssGWAS) for 6-week body weight in broiler chickens.Genome-wide marker-assisted selection combining all pedigree phenotypic information with genotypic data in one step: An example using broiler chickens.Genomic variation and population structure detected by single nucleotide polymorphism arrays in Corriedale, Merino and Creole sheep.Multiple-trait genomic evaluation of linear type traits using genomic and phenotypic data in US Holsteins.Efficient computation of the genomic relationship matrix and other matrices used in single-step evaluation.Breeding and Genetics Symposium: really big data: processing and analysis of very large data sets.Changes in variance explained by top SNP windows over generations for three traits in broiler chicken.Accuracy of estimated breeding values with genomic information on males, females, or both: an example on broiler chickenAncestral Relationships Using Metafounders: Finite Ancestral Populations and Across Population Relationships.Genome-wide association between single nucleotide polymorphisms with beef fatty acid profile in Nellore cattle using the single step procedure.Weighting Strategies for Single-Step Genomic BLUP: An Iterative Approach for Accurate Calculation of GEBV and GWASTechnical note: Acceleration of sparse operations for average-information REML analyses with supernodal methods and sparse-storage refinements.Genomic prediction for tick resistance in Braford and Hereford cattle.Genotype by environment interaction for tick resistance of Hereford and Braford beef cattle using reaction norm models.Hot topic: a unified approach to utilize phenotypic, full pedigree, and genomic information for genetic evaluation of Holstein final score.Implementation of genomic recursions in single-step genomic best linear unbiased predictor for US Holsteins with a large number of genotyped animals.Use of genomic recursions and algorithm for proven and young animals for single-step genomic BLUP analyses--a simulation study.Quality control of genotypes using heritability estimates of gene content at the marker.Application of single step genomic BLUP under different uncertain paternity scenarios using simulated data.Methods for genomic evaluation of a relatively small genotyped dairy population and effect of genotyped cow information in multiparity analyses.Short communication: genetic trends of milk yield under heat stress for US Holsteins.Are evaluations on young genotyped animals benefiting from the past generations?Implications of SNP weighting on single-step genomic predictions for different reference population sizes.Methods to approximate reliabilities in single-step genomic evaluation.Genetic evaluation using single-step genomic best linear unbiased predictor in American Angus.Hot topic: Use of genomic recursions in single-step genomic best linear unbiased predictor (BLUP) with a large number of genotypes.Using recursion to compute the inverse of the genomic relationship matrix.Unknown-parent groups in single-step genomic evaluation.Analyses of reaction norms reveal new chromosome regions associated with tick resistance in cattle.Bias in genomic predictions for populations under selection.Prediction accuracy for a simulated maternally affected trait of beef cattle using different genomic evaluation models.Frequentist p-values for large-scale-single step genome-wide association, with an application to birth weight in American Angus cattle.Resource allocation optimization with multi-trait genomic prediction for bread wheat (Triticum aestivum L.) baking quality.Genetic evaluation of growth in a multibreed beef cattle population using random regression-linear spline modelsEvaluation of a multi-line broiler chicken population using a single-step genomic evaluation procedureMultiple trait genomic evaluation of conception rate in HolsteinsEvaluation of the utility of diagonal elements of the genomic relationship matrix as a diagnostic tool to detect mislabelled genotyped animals in a broiler chicken populationShort communication: Methods to compute genomic inbreeding for ungenotyped individualsEffects of ignoring inbreeding in model-based accuracy for BLUP and SSGBLUPWhole Genome Mapping Reveals Novel Genes and Pathways Involved in Milk Production Under Heat Stress in US Holstein Cows
P50
Q33658640-D37EB7FB-A48D-4B9A-8DC7-1AD28326883BQ33708664-6A260DC4-6C28-43A8-8FD7-8EE2D5EECF2AQ33890359-EEA8E1EA-CA01-4234-BEA5-6CF478B34976Q33970728-FC8B2137-B74D-4AC4-87B2-5A877E79E0EDQ34068685-6FEC2465-E0E0-4A79-BA58-E4B6338389D4Q34078814-2F65941B-5B99-4506-BA96-6F37A8486031Q34272486-DB44F800-AEE1-43DE-9A72-BC0023B0A5CFQ35806649-C3B05ABB-F5F7-410A-BDBC-78E50803790CQ35821052-4F84F13D-524C-49F4-981D-9F40BC2F9088Q35951589-3DE5D209-79F6-4E07-BB2B-13BDAC7E7A3DQ37188044-A9A33D3D-0E48-4122-BFE1-8EAEC5E5F67AQ38411484-8F22DF9B-D0E6-4F0E-9AD3-6ED562D78EC8Q38931949-7E5D8415-45E6-4C10-9899-95AAA041763AQ39274322-987439EE-AED6-42D0-B142-E566A7563E6EQ39906136-44AE76A9-4359-4AF2-8E0E-3A16BE53F00BQ40066833-A8C9C291-4EA4-4BC0-B54B-625664C60341Q41096907-692DF54F-3286-46D1-91FC-A42A7BE8ADB7Q41610964-D1E1B18D-B6BD-42D5-9648-BA8E086C940AQ42366170-841EADC0-41B3-4DA8-B9B8-662F7A989916Q45266854-4305EF84-49F9-4473-AF93-09BA632648BDQ46367872-32376008-347A-4151-B335-1FBD33F17134Q46912793-4ECDCA3F-57AF-4C6F-ADD2-C24DBA4A3A60Q48191810-EC0018FF-366C-4B1A-9EEB-0A99160E5825Q49052715-1A565F73-3B35-41F4-9F3C-4F5F272C5B2BQ50892316-F9051AD3-5A5D-467F-89ED-C3AC7ABC8707Q50933240-2601F19C-BAC1-48B5-9392-5C42078D85F2Q51098849-6E48196E-05C0-4F31-942E-6732F4DEA3F3Q51186410-B0A8BD9A-7652-49D4-AFB7-410262D833ACQ52579145-8AA37D9C-8684-41DE-9542-261FDDA479ABQ53086783-025C6739-9614-4D2C-815B-D71138CF9F60Q53123513-C8466E39-8771-431D-9277-05AD7DDF6655Q64882781-6E45D6CB-9151-4053-A21B-0B81A28B9CC7Q64963347-4A6FE954-A10C-4151-BAEC-90B49C642E9DQ81509338-80D94A27-9C06-4596-B41F-D79AAD9F1DAEQ83190727-D2F35EFB-1C94-43E4-B2C5-F46D16B8BB51Q83982347-664D9719-9764-427B-BEC0-DE7E57C8E524Q84926069-C1E17406-B549-45E3-B8FB-F421B6B2A1DAQ89711826-45697D48-BD9B-46C8-BB90-8C32002E9F3EQ89813984-05CB0155-0CC8-4137-B40E-C546FD3E3704Q90861055-ADD10A56-FF5E-4587-9EE7-59C74807872F
P50
description
onderzoeker
@nl
researcher ORCID ID = 0000-0002-1038-4752
@en
name
Ignacio Aguilar
@ast
Ignacio Aguilar
@en
Ignacio Aguilar
@es
Ignacio Aguilar
@nl
type
label
Ignacio Aguilar
@ast
Ignacio Aguilar
@en
Ignacio Aguilar
@es
Ignacio Aguilar
@nl
prefLabel
Ignacio Aguilar
@ast
Ignacio Aguilar
@en
Ignacio Aguilar
@es
Ignacio Aguilar
@nl
P106
P1153
23488048300
P21
P31
P496
0000-0002-1038-4752