Similarity Measures Based on the Overlap of Ranked Genes Are Effective for Comparison and Classification of Microarray Data.
Fabrizio SerraChiara RomualdiFederico FogolariPublished in: J. Comput. Biol. (2016)
Keyphrases
- microarray data
- microarray data analysis
- dna microarray data
- microarray
- gene expression
- microarray datasets
- informative genes
- cancer classification
- gene selection
- gene expression data
- relevant genes
- feature selection
- gene expression profiles
- small number of samples
- dna microarray
- similarity measure
- colon cancer
- microarray gene expression data
- data sets
- high dimensional
- gene networks
- cluster analysis
- feature vectors
- gene expression analysis
- biologically significant
- meta analysis
- microarray analysis
- gene expression data sets
- differentially expressed genes
- high throughput
- selected genes
- biologically relevant
- analysis of gene expression
- gene function prediction
- high dimensionality
- gene expression microarray data
- cancer diagnosis
- gene clusters
- gene expression datasets
- feature space
- biological data
- gene sets
- machine learning
- decision trees
- supervised learning
- regulatory networks
- gene regulatory networks
- ovarian cancer
- support vector machine svm
- gene expression patterns
- microarray technology
- saccharomyces cerevisiae
- biological information