Bayesian variable selection for linear regression in high dimensional microarray data.
Wellington CabreraCarlos OrdonezDavid Sergio MatusevichVeerabhadran BaladandayuthapaniPublished in: DTMBIO (2013)
Keyphrases
- variable selection
- linear regression
- microarray data
- high dimensional
- least squares
- input variables
- gene selection
- low dimensional
- linear models
- gene function prediction
- dimension reduction
- dimensionality reduction
- regression problems
- high dimensional data
- microarray classification
- gene expression data
- gene expression microarray data
- data points
- feature space
- high dimensionality
- maximum likelihood
- bayesian inference
- microarray datasets
- bayesian networks
- microarray
- kernel function
- nearest neighbor
- ls svm
- feature selection
- gene expression profiles
- feature extraction