Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Strategies for choosing core animals in the algorithm for proven and young and their impact on the accuracy of single-step genomic predictions in cattle.

Animal : an international journal of animal bioscience - 1 Apr 2023

Cesarani A, Bermann M, Dimauro C, Degano L, Vicario D, Lourenco D, Macciotta N P P

Abstract excerpt

Nowadays, in some populations, the number of genotyped animals is too large to obtain the inverse of the genomic relationship matrix. The algorithm for proven and young animals (APY) can be used to overcome this problem. In the present work, different strategies for defining core animals in APY were tested using either simulated or real data. In particular, core definitions based on random choice or on the...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Algorithms
Share to Cattle

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Genome

Share to Genomics

Share to Genotype

Share to Models, Genetic

Share to Phenotype

Source

Identifiers

PMID: 37001441
DOI: 10.1016/j.animal.2023.100766

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Strategies for choosing core animals in the algorithm for proven and young and their impact on the accuracy of single-step genomic predictions in cattle.PMID 37001441Read ↗

A comprehensive study on size and definition of the core group in the proven and young algorithm for single-step GBLUP.Semantic proximity Read ↗

Core-dependent changes in genomic predictions using the Algorithm for Proven and Young in single-step genomic best linear unbiased prediction.Semantic proximity Read ↗

On the equivalence between marker effect models and breeding value models and direct genomic values with the Algorithm for Proven and Young.Semantic proximity Read ↗

Optimisation of the core subset for the APY approximation of genomic relationships.Semantic proximity Read ↗

Sparse single-step genomic BLUP in crossbreeding schemes.Semantic proximity Read ↗

Dimensionality of genomic information and performance of the Algorithm for Proven and Young for different livestock species.Semantic proximity Read ↗

Short communication: Genomic prediction using different single-step methods in the Finnish red dairy cattle population.Semantic proximity Read ↗

Indirect predictions with a large number of genotyped animals using the algorithm for proven and young.Semantic proximity Read ↗

Sparse single-step method for genomic evaluation in pigs.Semantic proximity Read ↗

Hot topic: Use of genomic recursions in single-step genomic best linear unbiased predictor (BLUP) with a large number of genotypes.Semantic proximity Read ↗

Is single-step genomic REML with the algorithm for proven and young more computationally efficient when less generations of data are present?Semantic proximity Read ↗

Use of principal component approach to predict direct genomic breeding values for beef traits in Italian Simmental cattle.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.