Bayesian optimization of multivariate genomic prediction models based on secondary traits for improv...
Bayesian optimization of multivariate genomic prediction models based on secondary traits for improved accuracy gains and phenotyping costs
About this item
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Author / Creator
Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
Journal title
Language
English
Formats
Publication information
Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
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More information
Scope and Contents
Contents
Key message
We propose a novel approach to the Bayesian optimization of multivariate genomic prediction models based on secondary traits to improve accuracy gains and phenotyping costs via efficient Pareto frontier estimation.
Multivariate genomic prediction based on secondary traits, such as data from various omics technologies including hig...
Alternative Titles
Full title
Bayesian optimization of multivariate genomic prediction models based on secondary traits for improved accuracy gains and phenotyping costs
Authors, Artists and Contributors
Author / Creator
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Record Identifier
TN_cdi_proquest_miscellaneous_2579380887
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_2579380887
Other Identifiers
ISSN
0040-5752
E-ISSN
1432-2242
DOI
10.1007/s00122-021-03949-1
