Mixture-model based estimation of gene expression variance from public database improves identification of differentially expressed genes in small sized microarray data.
Mingoo KimSung-Bum ChoJu Han KimPublished in: Bioinform. (2010)
Keyphrases
- differentially expressed genes
- microarray data
- gene expression
- microarray
- database
- gene expression data
- differentially expressed
- microarray data analysis
- meta analysis
- gene selection
- biological processes
- gene expression patterns
- high throughput
- data sets
- gene expression profiles
- analysis of gene expression
- feature selection
- microarray datasets
- regulatory networks
- cancer classification
- gene networks
- transcription factors
- high dimensional
- gene regulation
- cluster analysis
- gene clusters
- gene expression analysis
- binding sites
- microarray technology
- biological data
- molecular biology
- statistically significant
- dna microarray
- high dimensionality
- computational methods
- colon cancer