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BACKGROUND In the study of associations between genomic data and complex phenotypes there may be relationships that are not amenable to parametric statistical modeling. Such associations have been investigated mainly using single-marker and Bayesian linear regression models that differ in their distributions, but that assume additive inheritance while(More)
Bayesian regularization of artificial neural networks (BRANNs) were used to predict body mass index (BMI) in mice using single nucleotide polymorphism (SNP) markers. Data from 1896 animals with both phenotypic and genotypic (12 320 loci) information were used for the analysis. Missing genotypes were imputed based on estimated allelic frequencies, with no(More)
Different data sources were used to examine hypothesized relations among neighborhood-, family-, and individual-level variables, and perceptions of neighborhood collective efficacy. Data were from 1,105 individuals (56% female, 42% African American, and 58% White) nested within 55 neighborhoods and 392 families, analyzed within a multilevel design using a(More)
Artificial neural networks (ANN) mimic the function of the human brain and are capable of performing massively parallel computations for data processing and knowledge representation. ANN can capture nonlinear relationships between predictors and responses and can adaptively learn complex functional forms, in particular, for situations where conventional(More)
Genetic parameters for prolificacy traits for Columbia (COLU), Polypay (POLY), Rambouillet (RAMB), and Targhee (TARG) breeds of sheep were estimated with REML using animal models. Traits were number of live births (LAB), litter size at birth (LSB) and weaning (LSW), and litter weight weaned (LWW). Numbers of observations ranged from 5,140 to 7,095 for(More)
Genotype imputation is an important tool for whole-genome prediction as it allows cost reduction of individual genotyping. However, benefits of genotype imputation have been evaluated mostly for linear additive genetic models. In this study we investigated the impact of employing imputed genotypes when using more elaborated models of phenotype prediction.(More)
Correlations between genetic expression in lambs when dams were young (1 yr), middle-aged (2 and 3 yr), or older (older than 3 yr) were estimated with three-trait analyses for weight traits. Weights at birth (BWT) and weaning (WWT) and ADG from birth to weaning were used. breeds of sheep, respectively. When averaged, relative estimates for WWT and ADG were(More)
Correlations between genetic expression in lambs when dams were young (1 yr), middle-aged (2 and 3 yr), or older (older than 3 yr) were estimated with three-trait analyses for weight traits. Weights at birth (BWT) and weaning (WWT) and ADG from birth to weaning were used. Numbers of observations were 7,731, 9,518, 9,512, and 9,201 for Columbia (COLU),(More)
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