A Bayesian model for genomic prediction using metabolic networks

Abstract Motivation Genomic prediction is now an essential technique in breeding and medicine, it interesting to see how omics data can be used improve accuracy. Precedent work proposed a metabolic network-based method biomass of Arabidopsis; however, the consists multiple steps that possibly degrade Results We Bayesian model integrates all jointly infers fluxes reactions related production. The showed higher accuracies than methods compared both simulated real data. findings support previous excellent idea network information for prediction. Availability All R stan scripts reproduce results this study are available at https://github.com/Onogi/MetabolicModeling Supplementary Table provided journal web site.