Simianer, Henner

[["dc.bibliographiccitation.artnumber","jkac226"],["dc.bibliographiccitation.journal","G3 Genes|Genomes|Genetics"],["dc.contributor.author","Westhues, Cathy C"],["dc.contributor.author","Simianer, Henner"],["dc.contributor.author","Beissinger, Timothy M"],["dc.contributor.editor","de los Campos, G"],["dc.date.accessioned","2022-10-04T10:22:15Z"],["dc.date.available","2022-10-04T10:22:15Z"],["dc.date.issued","2022"],["dc.description.abstract","Abstract\n We introduce the R-package learnMET, developed as a flexible framework to enable a collection of analyses on multi-environment trial breeding data with machine learning-based models. learnMET allows the combination of genomic information with environmental data such as climate and/or soil characteristics. Notably, the package offers the possibility of incorporating weather data from field weather stations, or to retrieve global meteorological datasets from a NASA database. Daily weather data can be aggregated over specific periods of time based on naive (for instance, nonoverlapping 10-day windows) or phenological approaches. Different machine learning methods for genomic prediction are implemented, including gradient-boosted decision trees, random forests, stacked ensemble models, and multilayer perceptrons. These prediction models can be evaluated via a collection of cross-validation schemes that mimic typical scenarios encountered by plant breeders working with multi-environment trial experimental data in a user-friendly way. The package is published under an MIT license and accessible on GitHub."],["dc.identifier.doi","10.1093/g3journal/jkac226"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/114625"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-600"],["dc.relation.eissn","2160-1836"],["dc.title","learnMET: an R package to apply machine learning methods for genomic prediction using multi-environment trial data"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]