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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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主要な著者: Paulino Pérez‐Rodríguez, Samuel Flores‐Galarza, Humberto Vaquera‐Huerta, David Hebert del Valle‐Paniagua, Osval A. Montesinos‐López, José Crossa
フォーマット: Artigo
言語:Inglês
出版事項: Wiley 2020-07-01
シリーズ:The Plant Genome
オンライン・アクセス:https://doi.org/10.1002/tpg2.20021
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