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

Genomic predictions for economically important traits in Brazilian Braford and Hereford beef cattle using true and imputed genotypes.

BMC genetics - 18 Jan 2017

Piccoli Mario L, Brito Luiz F, Braccini José, Cardoso Fernando F, Sargolzaei Mehdi, Schenkel Flávio S

Abstract excerpt

BACKGROUND: Genomic selection (GS) has played an important role in cattle breeding programs. However, genotyping prices are still a challenge for implementation of GS in beef cattle and there is still a lack of information about the use of low-density Single Nucleotide Polymorphisms (SNP) chip panels for genomic predictions in breeds such as Brazilian Braford and Hereford. Therefore, this study investigated the...

Read the complete abstract on PubMed

Topics

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

Share to Breeding
Share to Cattle

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Genomics

Share to Genotype

Share to Machine Learning

Share to Phenotype

Share to Species Specificity

Source

Open in PubMed Open full text

Identifiers

PMID: 28100165
DOI: 10.1186/s12863-017-0475-9
PMCID: PMC5241971

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 5 Sept 2026. Manifest publication-graph-cohort-2026-09-05.1.

Source receipt: pubmed, retrieved 5 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Genomic predictions for economically important traits in Brazilian Braford and Hereford beef cattle using true and imputed genotypes.PMID 28100165Read ↗

Improving accuracy of genomic prediction in Brangus cattle by adding animals with imputed low-density SNP genotypes.Semantic proximity Read ↗

Genomic prediction in French Charolais beef cattle using high-density single nucleotide polymorphism markers.Semantic proximity Read ↗

Improving Genomic Predictions in Multi-Breed Cattle Populations: A Comparative Analysis of BayesR and GBLUP Models.Semantic proximity Read ↗

Accuracy of predicting genomic breeding values for residual feed intake in Angus and Charolais beef cattle.Semantic proximity Read ↗

The impact of training strategies on the accuracy of genomic predictors in United States Red Angus cattle.Semantic proximity Read ↗

Accuracy of genome-wide imputation in Braford and Hereford beef cattle.Semantic proximity Read ↗

Strategies for genomic predictions of an indicine multi-breed population using single-step GBLUP.Semantic proximity Read ↗

Accuracy of genomic predictions for feed efficiency traits of beef cattle using 50K and imputed HD genotypes.Semantic proximity Read ↗

Genome-Enabled Prediction of Breeding Values for Feedlot Average Daily Weight Gain in Nelore Cattle.Semantic proximity Read ↗

Accuracy of genomic predictions in Bos indicus (Nellore) cattle.Semantic proximity Read ↗

Genomic prediction using imputed whole-genome sequence data in Holstein Friesian cattle.Semantic proximity Read ↗

Development of genomic predictions for Angus cattle in Brazil incorporating genotypes from related American sires.Semantic proximity Read ↗

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