David Hobby

This study compares genomic prediction methods for multiple time-resolved traits in maize, finding MegaLMM excels in snapshot accuracy while dynamicGP is better for longitudinal accuracy.

KineticGP improves prediction of leaf photosynthesis traits in maize by integrating genomic data with kinetic models of C4 photosynthesis.

This paper classifies and compares multi-trait genomic prediction models using an Oryza sativa diversity panel to identify strengths and limitations of existing approaches.