Anders Skaarud

Bayesian genomic models boost prediction accuracy for resistance against Streptococcus agalactiae in Nile tilapia (Oreochromus nilioticus)

The paper evaluates Bayesian genomic models for predicting resistance to Streptococcus agalactiae in Nile tilapia, finding improved prediction accuracy compared to pedigree-based models.

Genomic prediction for commercial traits using univariate and multivariate approaches in Nile tilapia (Oreochromis niloticus)

This study compares genomic and pedigree-based models for predicting commercial traits in Nile tilapia, finding genomic models significantly improve prediction accuracy and reduce bias.