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

Machine learning classification procedure for selecting SNPs in genomic selection: application to early mortality in broilers.

Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie - 1 Dec 2007

Long N, Gianola D, Rosa G J M, Weigel K A, Avendaño S

Abstract excerpt

Genome-wide association studies using single nucleotide polymorphisms (SNPs) can identify genetic variants related to complex traits. Typically thousands of SNPs are genotyped, whereas the number of phenotypes for which there is genomic information may be smaller. When predicting phenotypes, opti...

Read the complete abstract on PubMed

Topics

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

Share to Artificial Intelligence
Share to Case-Control Studies
Share to Chickens

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Gene Frequency

Share to Genome

Share to Heterozygote

Share to Longevity

Share to Selection, Genetic

Source

Identifiers

PMID: 18076475
DOI: 10.1111/j.1439-0388.2007.00694.x

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 2 Sept 2026. Prepared record publication-18076475-2026-09-02.2. Manifest publication-graph-cohort-2026-09-02.2.

Source receipt: PubMed via Helena Literature Corpus, retrieved 2 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Machine learning classification procedure for selecting SNPs in genomic selection: application to early mortality in broilers.PMID 18076475Read ↗

Machine learning classification procedure for selecting SNPs in genomic selection: application to early mortality in broilers.Semantic proximity Read ↗

Comparison of classification methods for detecting associations between SNPs and chick mortality.Semantic proximity Read ↗

Genome-wide marker-assisted selection combining all pedigree phenotypic information with genotypic data in one step: An example using broiler chickens.Semantic proximity Read ↗

Marker-assisted assessment of genotype by environment interaction: a case study of single nucleotide polymorphism-mortality association in broilers in two hygiene environments.Semantic proximity Read ↗

Temporal dynamics of genetic parameters and SNP effects for performance and disorder traits in poultry undergoing genomic selection.Semantic proximity Read ↗

Nonparametric methods for incorporating genomic information into genetic evaluations: an application to mortality in broilers.Semantic proximity Read ↗

Integrating Bioinformatics and Machine Learning for Genomic Prediction in Chickens.Semantic proximity Read ↗

Genome-wide prediction of discrete traits using Bayesian regressions and machine learning.Semantic proximity Read ↗

A predictive assessment of genetic correlations between traits in chickens using markers.Semantic proximity Read ↗

Identification of population-informative markers from high-density genotyping data through combined feature selection and machine learning algorithms: Application to European autochthonous and cosmopolitan pig breeds.Semantic proximity Read ↗

Restriction site-associated DNA sequencing technologies as an alternative to low-density SNP chips for genomic selection: a simulation study in layer chickens.Semantic proximity Read ↗

Effect of allele frequencies, effect sizes and number of markers on prediction of quantitative traits in chickens.Semantic proximity Read ↗

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