Maria Lie Selle

This paper introduces a Bayesian method that improves genomic modeling by incorporating expert knowledge through prior distributions, enhancing robustness and selection accuracy in plant breeding.

This study shows spatial modelling improves genetic evaluation in smallholder dairy cattle systems by better separating genetic and environmental effects.

This paper introduces a hierarchical model to estimate haplotype effects using phylogenetic relationships, showing improved estimates with sparse modeling and better performance in low-observation scenarios.

This paper compares spatial models for agricultural field trials using INLA, showing AR1⊗AR1 and SPDE models provide best predictive performance with or without genomic data.

This paper proposes a genomic selection model that incorporates SNP-specific variance predictors, showing improved accuracy compared to traditional methods.