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

Prediction of breed composition in an admixed cattle population.

Animal genetics - 1 Dec 2012

Frkonja A, Gredler B, Schnyder U, Curik I, Sölkner J

Abstract excerpt

Swiss Fleckvieh was established in 1970 as a composite of Simmental (SI) and Red Holstein Friesian (RHF) cattle. Breed composition is currently reported based on pedigree information. Information on a large number of molecular markers potentially provides more accurate information. For the analysis, we used Illumina BovineSNP50 Genotyping Beadchip data for 90 pure SI, 100 pure RHF and 305 admixed bulls. The scope...

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
Share to Genetic Markers

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Genome

Share to Hybridization, Genetic

Share to Markov Chains

Share to Models, Genetic

Share to Selection, Genetic

Source

Identifiers

PMID: 23061480
DOI: 10.1111/j.1365-2052.2012.02345.x

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

Prediction of breed composition in an admixed cattle population.PMID 23061480Read ↗

Locus-specific ancestry to detect recent response to selection in admixed Swiss Fleckvieh cattle.Semantic proximity Read ↗

Predicting breed composition using breed frequencies of 50,000 markers from the US Meat Animal Research Center 2,000 Bull Project.Semantic proximity Read ↗

Combined use of principal component analysis and random forests identify population-informative single nucleotide polymorphisms: application in cattle breeds.Semantic proximity Read ↗

Tracing cattle breeds with principal components analysis ancestry informative SNPs.Semantic proximity Read ↗

Interpretable machine learning for cattle breed classification and SNP prioritization.Semantic proximity Read ↗

Estimation of genomic breed composition of individual animals in composite beef cattle.Semantic proximity Read ↗

Parsimonious model for analyzing parent-of-origin effects related to beef traits in dual-purpose Simmental.Semantic proximity Read ↗

The evaluation of the usefulness of pedigree verification-dedicated SNPs for breed assignment in three polish cattle populations.Semantic proximity Read ↗

BIBI: Bayesian inference of breed composition.Semantic proximity Read ↗

Breed assignment of Italian cattle using biallelic AFLP markers.Semantic proximity Read ↗

Unraveling genetic admixture in the Indian crossbred cattle by different approaches using Bovine 50K BeadChip.Semantic proximity Read ↗

The use of a genomic relationship matrix for breed assignment of cattle breeds: comparison and combination with a machine learning method.Semantic proximity Read ↗

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