Bayesian neural networks with variable selection for prediction of genotypic values
Abstract Background Estimating the genetic component of a complex phenotype is a complicated problem, mainly because there are many allele effects to estimate from a limited number of phenotypes. In spite of this difficulty, linear methods with variable selection have been able to give good predicti...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | deu |
| Published: |
BMC
2020-05-01
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| Series: | Genetics Selection Evolution |
| Online Access: | http://link.springer.com/article/10.1186/s12711-020-00544-8 |