Article
Predicting complex quantitative traits with Bayesian neural networks: a case study with Jersey cows and wheat.
BMC genetics - 7 Oct 2011
Gianola Daniel, Okut Hayrettin, Weigel Kent A, Rosa Guilherme Jm
Abstract excerpt
BACKGROUND: In the study of associations between genomic data and complex phenotypes there may be relationships that are not amenable to parametric statistical modeling. Such associations have been investigated mainly using single-marker and Bayesian linear regression models that differ in their distributions, but that assume additive inheritance while ignoring interactions and non-linearity. When interactions...
Topics
- Animals
- Bayes Theorem
- Cattle
- Genetic Markers
- Genotype
- Milk
- Models, Genetic
- Models, Statistical
- Neural Networks, Computer
- Phenotype
- Polymorphism, Single Nucleotide
- Quantitative Trait, Heritable
- Regression Analysis
- Triticum