A comparison of methods for training population optimization in ...

This work aimed to provide an extensive benchmark among optimization methods and optimal training set size by testing a wide range of them in seven datasets.

Maximizing CDmean and Avg_GRM_self were the best criteria for training set optimization. A training set size of 50-55% (targeted) or 65-85% ...

(PDF) A comparison of methods for training population optimization ...

The literature described many training set optimization methods, but there is a lack of a comprehensive comparison among them. ... Our results ...

A comparison of methods for training population optimization in ...

A comparison of methods for training population optimization in genomic selection. Genomic selection is a breeding tool which employs genomic ...

A comparison of methods for training population optimization in ...

Abstract: With the advent of genomic selection (GS) as a widespread breeding tool, mechanisms to efficiently design an optimal training set for GS models became ...

A comparison of methods for training population optimization in ...

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Selection, Genetic / Models, Genetic Type of study: Prognostic_studies Language: ...

A comparison of methods for training set optimization in genomic ...

(2015) Genomic selection and association mapping in rice (Oryza sativa): effect of trait genetic architecture, training population composition, ...

[PDF] Training set optimization under population structure in ...

A comparison of methods for training population optimization in genomic selection · Biology, Computer Science. Theoretical and Applied Genetics · 2023.

Christian Dreischer on LinkedIn: A comparison of methods for ...

Christian Dreischer's Post · A comparison of methods for training population optimization in genomic selection - PubMed · More Relevant Posts · ggkegg: analysis ...

Training Population Optimization for Genomic Selection - PubMed

Training populations can be optimized for specific testing populations. Optimized training populations are smaller, more related, and more predictive.

Training Population Optimization for Genomic Selection - ACSESS

Several within-TR optimization strategies were compared to identify groups of individuals with increased predictive ability. Additionally, ...

Training population optimization for genomic selection improves the ...

Request PDF | Training population optimization for genomic selection improves the predictive ability of a costly measure in bread wheat, the gliadin to ...

A Modified Bayesian Optimization Approach for Determining a ...

Some training set optimization methods developed for achieving maximal Pearson's correlation were employed for comparison, including a ranking ...

Evaluation of strategies to optimize training populations for genomic ...

In this paper, we focus on the optimization criteria: genetic diversity, phenotypic variance and genetic similarity between the training and testing populations ...

Training population optimization for genomic selection improves the ...

A comparison of methods for training population optimization in genomic selection · Biology, Computer Science. Theoretical and Applied Genetics · 2023.

Genomic selection optimization in blueberry: Data‐driven methods ...

In GS, a training population (TRS) composed of a set of individuals within the breeding program is utilized to calibrate the relationship ...

Training Population Optimization for Genomic Selection in Miscanthus

Ultimately, these results suggest that the ideal training set should contain the same causal mutations segregating within interspecific M×g populations, and ...

Design of training populations for selective phenotyping in genomic ...

In this paper, we compared the performance of four optimization methods under two scenarios (U-Opt and T-Opt) on two datasets and 13 traits. In ...

Training optimization in genomic selection: A comparison of algorithms

Only genotypic information is available in this population. Empirical and simulation studies have shown than GS performed better than traditional methods. ( ...

Optimization of genomic selection training populations with a ...

Our results show that, compared to a random sample of the same size, the use of a set of individuals selected by our method improved accuracies.