Maximizing the reusability of gene expression data by predicting missing metadata.
Pei-Yau LungDongrui ZhongXiaodong PangYan LiJinfeng ZhangPublished in: PLoS Comput. Biol. (2020)
Keyphrases
- gene expression data
- metadata
- learning objects
- gene expression
- microarray
- microarray data
- gene expression analysis
- data sets
- gene regulatory networks
- gene networks
- gene expression data analysis
- missing data
- dna microarray
- gene selection
- high dimensionality
- microarray gene expression data
- high dimensional data
- analysis of gene expression data
- dna microarray data
- gene expression data sets
- yeast cell cycle
- feature selection
- tumor classification
- gene expression profiles
- regulatory networks
- database
- missing values
- cancer diagnosis
- cancer classification
- gene expression datasets
- gene expression profiling
- clustering gene expression data
- gene expression patterns
- pattern recognition
- decision trees
- high throughput
- feature extraction
- colon cancer