Determination of the Minimum Sample Size in Microarray Experiments to Cluster Genes Using K-means Clustering.
Fang-Xiang WuWen-Jun ZhangAnthony J. KusalikPublished in: BIBE (2003)
Keyphrases
- sample size
- microarray
- expression patterns
- gene expression
- microarray data
- gene expression data
- gene clusters
- high throughput
- expression levels of thousands of genes
- gene ontology
- differentially expressed genes
- microarray data analysis
- gene expression profiling
- experimental conditions
- gene expression analysis
- small sample size
- gene selection
- dna microarray
- cancer classification
- yeast cell cycle
- gene gene
- microarray technology
- gene networks
- microarray datasets
- gene expression profiles
- model selection
- biological processes
- gene expression data sets
- gene expression patterns
- molecular biology
- upper bound
- gene expression datasets
- microarray analysis
- regulatory networks
- high dimensionality
- gene expression levels
- analysis of gene expression
- microarray expression data
- clustering analysis
- worst case
- statistical tests
- colon cancer
- cancer diagnosis
- cluster analysis
- structure learning
- gene sets
- clustering algorithm
- genome wide
- related genes
- data sets
- genomic data
- data points
- decision trees
- gene regulatory networks
- biological networks
- data mining