AI Medical Compendium Journal:
The plant genome

Showing 11 to 13 of 13 articles

Improvement in genomic prediction of maize with prior gene ontology information depends on traits and environmental conditions.

The plant genome
Classical genomic prediction approaches rely on statistical associations between traits and markers rather than their biological significance. Biologically informed selection of genomic regions can help prioritize polymorphisms by considering underly...

Machine Learning as an Effective Method for Identifying True Single Nucleotide Polymorphisms in Polyploid Plants.

The plant genome
Single nucleotide polymorphisms (SNPs) have many advantages as molecular markers since they are ubiquitous and codominant. However, the discovery of true SNPs in polyploid species is difficult. Peanut ( L.) is an allopolyploid, which has a very low r...

Applications of Machine Learning Methods to Genomic Selection in Breeding Wheat for Rust Resistance.

The plant genome
New methods and algorithms are being developed for predicting untested phenotypes in schemes commonly used in genomic selection (GS). The prediction of disease resistance in GS has its own peculiarities: a) there is consensus about the additive natur...