Objective To screen for predictive obesity factors in overweight populations using an optimal
and interpretable machine learning algorithm. Methods This cross-sectional study was …

Background: Linking genotypic changes to phenotypic traits based on machine learning
methods has various challenges. In this study, we developed a workflow based on …

Background Cross-validation techniques in genetic evaluations encounter limitations due to
the unobservable nature of breeding values and the challenge of validating estimated …

Background Whole genome variants offer sufficient information for genetic prediction of
human disease risk, and prediction of animal and plant breeding values. Many sophisticated …

Genomic prediction (GP) has emerged an effective tool for addressing the many
shortcomings of traditional selective breeding, thereby enhancing the selection process. In …

Genomic selection methods are particularly useful for traits that are difficult or expensive to
measure. We investigated the impact of using predictor growth traits and/or genomic …

Feather pecking, related feather damage, and mortality are crucial welfare and efficiency
traits in laying hens. When individuals are kept in sib groups, genetic analysis of feather …

As genomic selection emerges as a promising breeding method for both plants and animals,
numerous methods have been introduced and applied to various real and simulated data …

Background Forest geneticists typically use provenances to account for population
differences in their improvement schemes; however, the historical records of the imported …

Genomic relationships can be computed with dense genome‐wide genotypes through
different methods, either based on identity‐by‐state (IBS) or identity‐by‐descent (IBD). The …