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

A Multi-Trait Gaussian Kernel Genomic Prediction Model under Three Tunning Strategies.

Genes - 3 Dec 2022

Kismiantini, Montesinos-López Abelardo, Cano-Páez Bernabe, Montesinos-López J Cricelio, Chavira-Flores Moisés, Montesinos-López Osval A, Crossa José

Abstract excerpt

While genomic selection (GS) began revolutionizing plant breeding when it was proposed around 20 years ago, its practical implementation is still challenging as many factors affect its accuracy. One such factor is the choice of the statistical machine learning method. For this reason, we explore the tuning process under a multi-trait framework using the Gaussian kernel with a multi-trait Bayesian Best Linear...

Read the complete abstract on PubMed

Topics

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

Share to Bayes Theorem
Share to Genomics

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Machine Learning

Share to Models, Genetic

Share to Phenotype

Source

Open in PubMed Open full text

Identifiers

PMID: 36553548
DOI: 10.3390/genes13122279
PMCID: PMC9778253

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 2 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

A Multi-Trait Gaussian Kernel Genomic Prediction Model under Three Tunning Strategies.PMID 36553548Read ↗

A Comparison between Three Tuning Strategies for Gaussian Kernels in the Context of Univariate Genomic Prediction.Semantic proximity Read ↗

A Comparison of Three Machine Learning Methods for Multivariate Genomic Prediction Using the Sparse Kernels Method (SKM) Library.Semantic proximity Read ↗

Advances in integrated genomic selection for rapid genetic gain in crop improvement: a review.Semantic proximity Read ↗

Multitrait genomic prediction method in approximate genome-based kernel model.Semantic proximity Read ↗

Genomic selection: Essence, applications, and prospects.Semantic proximity Read ↗

Understanding the genomic selection for crop improvement: current progress and future prospects.Semantic proximity Read ↗

GS4PB: An R Shiny application to facilitate a genomic selection pipeline for plant breeding.Semantic proximity Read ↗

Accounting for Correlation Between Traits in Genomic Prediction.Semantic proximity Read ↗

Overview of Genomic Prediction Methods and the Associated Assumptions on the Variance of Marker Effect, and on the Architecture of the Target Trait.Semantic proximity Read ↗

Genomic Selection in Plant Breeding: Methods, Models, and Perspectives.Semantic proximity Read ↗

Bayesian methods for jointly estimating genomic breeding values of one continuous and one threshold trait.Semantic proximity Read ↗

Sample size determination for training set optimization in genomic prediction.Semantic proximity Read ↗

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