Predicting phenotypes from high-dimensional genomes using gradient boosting decision trees
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3171341
Abstract: Genomic selection is an emerging technique for predicting unknown phenotypes using genome-wide marker coverage, allowing the use of efficient computational models to select individuals with high phenotypic values as candidate breeding populations. However, Genome Selection… read more here.
Keywords: gbdt; prediction; model; prediction accuracy ... See more keywords
Impact of epistasis effects on the accuracy of predicting phenotypic values of residual feed intake in U. S Holstein cows
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Genetics"
DOI: 10.3389/fgene.2022.1017490
Abstract: The impact of genomic epistasis effects on the accuracy of predicting the phenotypic values of residual feed intake (RFI) in U.S. Holstein cows was evaluated using 6215 Holstein cows and 78,964 SNPs. Two SNP models… read more here.
Keywords: accuracy predicting; heritability; epistasis effects; model ... See more keywords