… -of-the-art model such as single-trait ENET when predicting traits from SNPs and that they
outperform single-trait GBLUP for the population analyzed in this article. As evidenced by the …

… to analyze MCMC samples of covariance matrices, we use predicted (fitted) genomic values
and residuals from a multiple-trait … among maize traits and the comparison of networks with …

… agronomic traits in rice. We used a Bayesian network to depict conditional dependencies
among phenotypes, which can not be obtained by standard multi-trait analysis. We utilized …

… genetic information between traits over time allow Bayesian networks to offer … : Bayesian
network (BN), Pleiotropic Bayesian network (PBN), Dynamic Bayesian network (DBN), multi-trait …

… Bayesian network (Albert 2009) to find a more accurate overall estimate for each investigated
psychological personality trait (… simple examples with just one trait, the offered technique …

… observations and tissue collection for RNA-sequencing analysis were performed every four
… used to build the Bayesian network, we focus our attention on traits highly relevant to the …

… a Bayesian network to obtain a trait structure reflecting the genetic interdependency among
traits. Three directed paths were consistently identified by two Bayesian network algorithms. …

… network methodology to autistic traits. The aim of the present work is therefore to perform a
network analysis of the autistic traits … of the AQ with the Bayesian inference methods that have …

… Bayesian network consisting of a marker M, traits D directly associated with M, traits I indirectly
associated with M, and traits … Bayesian network for a cycle using an underlying Bayesian …

… a multi-trait Bayesian regression GWAS … traits. In this paper, we develop and implement
a new GWAS method called SEM-Bayesian alphabet, which integrates SEM to the multi-trait …