Cluster Association Rules to Discover Regulatory Genes from Gene Expression Data.
Chun-Liang LinDon-Lin YangHsin-Wei LinWei-Cheng LiaoPublished in: MLMTA (2007)
Keyphrases
- gene expression data
- association rules
- gene regulation
- expression patterns
- gene expression
- analysis of gene expression data
- microarray
- microarray data
- microarray gene expression data
- differentially expressed
- gene regulatory networks
- gene expression analysis
- yeast cell cycle
- gene clusters
- gene expression datasets
- microarray gene expression
- gene expression profiling
- gene selection
- data mining
- transcription factors
- data sets
- high dimensional
- regulatory networks
- clustering gene expression data
- high dimensionality
- gene networks
- clustering algorithm
- gene expression data analysis
- gene expression patterns
- feature selection
- cancer classification
- cancer diagnosis
- knowledge discovery
- dna microarray data
- high dimensional data
- gene expression data sets
- dna microarray
- saccharomyces cerevisiae
- microarray datasets
- gene ontology
- gene expression profiles
- informative genes
- microarray data analysis
- data mining techniques
- data points
- genomic data
- biological information
- biological knowledge
- tissue samples
- expression profiles
- protein interaction data
- data analysis