Abstract
Several methods have been used for genome-enabled prediction, where multiple regression models describe a target variable with a linear function of a set or subset of covariates. Bayesian Networks has offered interesting tools for a more parsimonious representation of the join distribution of a set of variables, which are useful for prediction purposes, e.g. using Markov Blanket (MB) of t…