A Phenotype-Driven Dimension Reduction (PhDDR) approach to integrated genomic association analyses.
Cuilan GaoCheng ChengPublished in: EMBC (2011)
Keyphrases
- dimension reduction
- principal component analysis
- high throughput
- high dimensional problems
- singular value decomposition
- feature extraction
- data mining and machine learning
- high dimensional
- high dimensional data
- variable selection
- linear discriminant analysis
- genome wide
- dimensionality reduction
- low dimensional
- random projections
- partial least squares
- manifold learning
- feature selection
- discriminative information
- high dimensional data analysis
- high dimensionality
- cluster analysis
- genotype phenotype
- feature space
- preprocessing
- unsupervised learning
- single nucleotide polymorphisms
- dimension reduction methods
- real world
- neural network
- pattern recognition
- genomic data
- similarity measure
- intrinsic dimension
- face recognition