Entropy-based gene ranking without selection bias for the predictive classification of microarray data.
Cesare FurlanelloMaria SerafiniStefano MerlerGiuseppe JurmanPublished in: BMC Bioinform. (2003)
Keyphrases
- microarray data
- microarray
- relevant genes
- gene selection
- dna microarray data
- microarray datasets
- cancer classification
- gene expression
- gene expression profiles
- small sample size
- gene expression data
- feature selection
- dna microarray
- microarray data analysis
- informative genes
- gene networks
- feature ranking
- microarray analysis
- colon cancer
- gene clusters
- gene expression analysis
- meta analysis
- cancer diagnosis
- microarray gene expression data
- high dimensionality
- biologically meaningful
- gene expression data sets
- cluster analysis
- high throughput
- gene expression patterns
- gene expression microarray data
- gene sets
- selected genes
- ovarian cancer
- data sets
- differentially expressed genes
- regulatory networks
- biological data
- small number of samples
- pattern recognition
- gene ontology
- microarray technology
- saccharomyces cerevisiae
- machine learning
- biologically significant
- high dimensional
- support vector machine
- supervised learning
- feature set
- gene regulatory networks
- decision trees
- text classification
- support vector machine svm