An effective hybrid approach of gene selection and classification for microarray data based on clustering and particle swarm optimisation.
Fei HanShanxiu YangJian GuanPublished in: Int. J. Data Min. Bioinform. (2015)
Keyphrases
- microarray data
- gene selection
- microarray data analysis
- cancer classification
- gene expression profiles
- microarray
- particle swarm optimisation
- relevant genes
- cluster analysis
- dna microarray data
- informative genes
- cancer diagnosis
- microarray datasets
- feature selection
- ovarian cancer
- gene expression
- dna microarray
- microarray analysis
- gene expression analysis
- gene expression data
- small number of samples
- microarray classification
- high dimensionality
- gene expression datasets
- high dimensional
- colon cancer
- feature ranking
- support vector machine svm
- selected genes
- clustering analysis
- biologically relevant
- feature space
- clustering method
- unsupervised learning
- pattern recognition
- neural network
- clustering algorithm
- differentially expressed genes
- support vector machine
- classification accuracy
- high throughput
- decision trees
- data sets
- feature extraction
- similarity measure
- gene ontology
- supervised learning
- dimensionality reduction
- fitness function
- machine learning methods