Ian Davis

Biology‐informed neural networks learn nonlinear representations from omics data to improve genomic prediction and biological discovery

Here, BINN is extended for genomic prediction and selection in crops by integrating thousands of single‐nucleotide polymorphisms with multi‐omics measurements and prior biological knowledge and substantially reduces prediction error relative to conventional neural nets and correctly identifies the most important nonlinear pathway.