Search
Search Results
-
A new strategy for using historical imbalanced yield data to conduct genome-wide association studies and develop genomic prediction models for wheat breeding
Using imbalanced historical yield data to predict performance and select new lines is an arduous breeding task. Genome-wide association studies...
-
Generalized Linear Models
In the generalized linear model (GLM) (which is not highly general) y = Xβ + ϵ, the response variables are normally distributed, with constant...
-
MSXFGP: combining improved sparrow search algorithm with XGBoost for enhanced genomic prediction
BackgroundWith the significant reduction in the cost of high-throughput sequencing technology, genomic selection technology has been rapidly...
-
A computationally efficient method for approximating reliabilities in large-scale single-step genomic prediction
BackgroundIn this study, computationally efficient methods to approximate the reliabilities of genomic estimated breeding values (GEBV) in a...
-
Exploring the potential of incremental feature selection to improve genomic prediction accuracy
BackgroundThe ever-increasing availability of high-density genomic markers in the form of single nucleotide polymorphisms (SNPs) enables genomic...
-
Interest of phenomic prediction as an alternative to genomic prediction in grapevine
BackgroundPhenomic prediction has been defined as an alternative to genomic prediction by using spectra instead of molecular markers. A reflectance...
-
Genomic prediction using machine learning: a comparison of the performance of regularized regression, ensemble, instance-based and deep learning methods on synthetic and empirical data
BackgroundThe accurate prediction of genomic breeding values is central to genomic selection in both plant and animal breeding studies. Genomic...
-
Multi-trait genomic prediction using in-season physiological parameters increases prediction accuracy of complex traits in US wheat
BackgroundRecently genomic selection (GS) has emerged as an important tool for plant breeders to select superior genotypes. Multi-trait (MT)...
-
Ensemble learning for integrative prediction of genetic values with genomic variants
BackgroundWhole genome variants offer sufficient information for genetic prediction of human disease risk, and prediction of animal and plant...
-
Sweet corn yield prediction using machine learning models and field-level data
The advent of modern technologies, acquisition of large amounts of crop management and weather data, and advances in computing are resha** modern...
-
Prediction of peptide mass spectral libraries with machine learning
The recent development of machine learning methods to identify peptides in complex mass spectrometric data constitutes a major breakthrough in...
-
psBLUP: incorporating marker proximity for improving genomic prediction accuracy
Genomic selection entails the estimation of phenotypic traits of interest for plants without phenotype based on the association between...
-
Genomic prediction of drought tolerance during seedling stage in maize using low-cost molecular markers
Drought tolerance in maize is a complex and polygenic trait, especially in the seedling stage. In plant breeding, complex genetic traits can be...
-
Confidence intervals for validation statistics with data truncation in genomic prediction
BackgroundValidation by data truncation is a common practice in genetic evaluations because of the interest in predicting the genetic merit of a set...
-
Genomic Prediction: Progress and Perspectives for Rice Improvement
Genomic prediction can be a powerful tool to achieve greater rates of genetic gain for quantitative traits if thoroughly integrated into a breeding...
-
Genomic Cross Prediction for Linseed Improvement
Crossing between two or more parents is a fundamental way to generate superior genetic variants through genetic recombination and transgressive...
-
scTour: a deep learning architecture for robust inference and accurate prediction of cellular dynamics
Despite the continued efforts, a batch-insensitive tool that can both infer and predict the developmental dynamics using single-cell genomics is...
-
Bayesian Genomic Linear Regression
The Bayesian paradigm for parameter estimation is introduced and linked to the main problem of genomic-enabled prediction to predict the trait of...
-
Enviromic-based kernels may optimize resource allocation with multi-trait multi-environment genomic prediction for tropical Maize
BackgroundSuccess in any genomic prediction platform is directly dependent on establishing a representative training set. This is a complex task,...
-
Building a Calibration Set for Genomic Prediction , Characteristics to Be Considered, and Optimization Approaches
The efficiency of genomic selection strongly depends on the prediction accuracy of the genetic merit of candidates. Numerous papers have shown that...