Identification of cancerous gene groups from microarray data by employing adaptive genetic and support vector machine technique.
Alok Kumar ShuklaPublished in: Comput. Intell. (2020)
Keyphrases
- microarray data
- gene selection
- microarray
- gene expression
- support vector machine
- gene expression data
- gene clusters
- relevant genes
- gene networks
- biologically meaningful
- dna microarray data
- meta analysis
- differentially expressed genes
- cluster analysis
- feature selection
- microarray gene expression data
- informative genes
- experimental conditions
- saccharomyces cerevisiae
- dna microarray
- cancer classification
- gene expression patterns
- microarray datasets
- gene sets
- data sets
- gene expression profiles
- regulatory networks
- microarray analysis
- biological data
- biologically significant
- gene expression analysis
- microarray data analysis
- high throughput
- high dimensional
- biologically relevant
- gene expression data sets
- gene ontology
- microarray technology
- high dimensionality
- biological knowledge
- small number of samples
- analysis of gene expression
- cancer diagnosis
- molecular biology
- data mining
- svm classifier
- feature space
- support vector
- training data