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Genome‐based prediction of Bayesian linear and non‐linear regression models for ordinal data
Abstract Linear and non‐linear models used in applications of genomic selection (GS) can fit different types of responses (e.g., continuous, ordinal, binary). In recent years, several genomic‐enabled prediction models have been developed for predicting complex traits in genomic‐assisted animal and p...
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Auteurs principaux: | , , , , , |
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Format: | Artigo |
Langue: | Inglês |
Publié: |
Wiley
2020-07-01
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Collection: | The Plant Genome |
Accès en ligne: | https://doi.org/10.1002/tpg2.20021 |
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