Extracting a biologically relevant latent space from cancer transcriptomes with variational autoencoders.
Gregory P. WayCasey S. GreenePublished in: PSB (2018)
Keyphrases
- biologically relevant
- latent space
- gene selection
- microarray data
- latent variables
- gene sets
- low dimensional
- microarray
- high dimensional
- gaussian process
- generative model
- gene expression data
- denoising
- biological networks
- image segmentation
- feature space
- gene ontology
- dimensionality reduction
- parameter space
- gene expression
- matrix factorization
- feature selection
- transfer learning
- support vector machine svm
- text classification
- data mining
- high dimensional data
- feature extraction
- collaborative filtering