A comprehensive evaluation of machine learning techniques for cancer class prediction based on microarray data.
Khalid RazaAtif N. HasanPublished in: Int. J. Bioinform. Res. Appl. (2015)
Keyphrases
- comprehensive evaluation
- microarray data
- gene selection
- biologically significant
- relevant genes
- microarray
- cancer classification
- dna microarray
- gene expression profiles
- microarray technology
- gene expression
- gene expression data
- gene expression data sets
- machine learning
- cancer diagnosis
- feature selection
- data sets
- colon cancer
- high dimensional
- microarray data analysis
- microarray gene expression data
- meta analysis
- gene sets
- microarray classification
- biological data
- biologically relevant
- machine learning methods
- cluster analysis
- analysis of gene expression
- ovarian cancer
- selected genes
- microarray datasets
- differentially expressed genes
- high throughput
- gene networks
- dna microarray data
- small number of samples
- gene expression microarray data
- breast cancer
- lung cancer
- biologically meaningful
- statistical methods
- tissue samples
- gene expression patterns
- gene expression datasets
- early detection
- informative genes
- gene expression analysis