Analyzing Alzheimer's disease gene expression dataset using clustering and association rule mining.
Benoit Le QueauM. Omair ShafiqReda AlhajjPublished in: IRI (2014)
Keyphrases
- association rule mining
- gene expression
- microarray
- gene expression profiles
- microarray gene
- functional genomics
- association rules
- gene expression data
- microarray data analysis
- differentially expressed genes
- microarray data
- gene expression analysis
- dna microarray
- microarray datasets
- gene interactions
- gene sets
- data mining techniques
- data mining
- biological processes
- clustering algorithm
- binding sites
- itemsets
- high dimensionality
- knowledge discovery
- pattern discovery
- biological networks
- gene expression patterns
- frequent itemset mining
- k means
- high throughput
- clustering method
- interesting patterns
- regulatory networks
- clustering analysis
- gene ontology
- cluster analysis
- biclustering algorithms
- databases
- actionable knowledge
- rule mining
- frequent itemsets
- interestingness measures
- high throughput technologies
- cluster ensemble
- transcription factors
- rule discovery
- database
- frequent patterns
- interesting rules
- gene regulatory networks
- protein interaction
- high dimensional
- feature selection
- data sets