High-Throughput GoMiner, an 'industrial-strength' integrative gene ontology tool for interpretation of multiple-microarray experiments, with application to studies of Common Variable Immune Deficiency (CVID).
Barry ZeebergHaiying QinSudarshan NarasimhanMargot SunshineHong CaoDavid W. KaneMark ReimersRobert M. StephensDavid BryantStanley K. BurtEldad ElnekaveDanielle M. HariThomas A. WynnCharlotte Cunningham-RundlesDonn M. StewartDavid NelsonJohn N. WeinsteinPublished in: BMC Bioinform. (2005)
Keyphrases
- microarray
- high throughput
- gene ontology
- gene expression
- gene expression data
- microarray data
- genome wide
- genomic data
- high dimensionality
- systems biology
- biological data
- gene selection
- experimental conditions
- gene expression analysis
- gene networks
- protein protein interactions
- microarray expression data
- cancer classification
- microarray data analysis
- gene sets
- microarray images
- microarray technology
- gene expression datasets
- dna microarray
- mass spectrometry
- gene expression profiles
- protein interaction
- molecular biology
- cancer diagnosis
- gene function
- gene expression levels
- high throughput technologies
- meta analysis
- text mining
- microarray datasets
- expression patterns
- analysis of gene expression
- low cost