Open access
Jul 2026
Using deep learning models as a genetic architecture for the simulation of breeding schemes
It is concluded that their ability to retain additive genetic variance depends on the models' architectural complexity, and when sufficiently complex, DL-based models exhibit greater retention of additive genetic variance.
Olumide Onabanjo, T. Meuwissen, H. M. Gjøen et al.
· G3 · 0 citations