Recursive Cluster Elimination (RCE) for classification and feature selection from gene expression data.
Malik YousefSegun JungLouise C. ShoweMichael K. ShowePublished in: BMC Bioinform. (2007)
Keyphrases
- gene expression data
- feature selection
- high dimensionality
- cancer classification
- microarray data
- microarray datasets
- gene expression
- microarray
- dna microarray data
- analysis of gene expression data
- gene expression analysis
- gene expression profiles
- classification accuracy
- dna microarray
- cancer diagnosis
- gene expression datasets
- feature space
- tumor classification
- gene expression data sets
- support vector machine
- gene expression microarray data
- gene selection
- text categorization
- microarray data analysis
- microarray gene expression data
- text classification
- support vector
- classification models
- colon cancer
- feature extraction
- gene regulatory networks
- data sets
- simultaneous clustering
- machine learning
- pattern recognition
- gene expression data analysis
- high dimensional
- tissue samples
- cancer datasets
- clustering algorithm
- gene expression profiling
- dimensionality reduction
- feature vectors
- regulatory networks
- feature ranking
- high dimensional data
- feature set
- training set
- database
- clustering gene expression data
- feature subset
- high throughput
- data points
- neural network