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Application of Response Surface Methods To Determine Conditions for Optimal Genomic Prediction
An epistatic genetic architecture can have a significant impact on prediction accuracies of genomic prediction (GP) methods. Machine learning methods predict traits comprised of epistatic genetic architectures more accurately than statistical methods based on additive mixed linear models. The differ...
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| Publicado no: | G3 (Bethesda) |
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| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Genetics Society of America
2017
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5592935/ https://ncbi.nlm.nih.gov/pubmed/28720710 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1534/g3.117.044453 |
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