2 citations · 3 across the 3 of their papers we have counts for
4 papers
A hybrid GPU/CPU implementation of the average information restricted maximum likelihood algorithm for fitting multivariate linear mixed models
Killian A. C. Melsen, Fred A. van Eeuwijk, Carel F. W. Peeters
The multivariate linear mixed model combined with restricted maximum likelihood estimation of (co)variance components and solving the mixed model equations is widely used for the a…
A latent factor approach to hyperspectral time series data for multivariate genomic prediction of grain yield in wheat
Jonathan F. Kunst, Killian A. C. Melsen, Willem Kruijer +4
High-dimensional time series phenotypic data is becoming increasingly common within plant breeding programmes. However, analysing and integrating such data for genetic analysis and…
REML implementations of kernel-based genomic prediction models for genotype x environment x management interactions
Killian A. C. Melsen, Salvador Gezan, Daniel J. Tolhurst +2
High-throughput pheno-, geno-, and envirotyping allows characterization of plant genotypes and the trials they are evaluated in, producing different types of data. These different…
Improving Genomic Prediction using High-dimensional Secondary Phenotypes: the Genetic Latent Factor Approach
Killian A. C. Melsen, Jonathan F. Kunst, José Crossa +4
Decreasing costs and new technologies have led to an increase in the amount of data available to plant breeding programs. High-throughput phenotyping (HTP) platforms routinely gene…