A Stationary Wavelet Entropy-Based Clustering Approach Accurately Predicts Gene Expression.
Nha NguyenAn P. N. VoInchan ChoiKyoung-Jae WonPublished in: J. Comput. Biol. (2015)
Keyphrases
- gene expression
- microarray
- gene expression profiles
- microarray gene
- gene expression data analysis
- gene expression analysis
- gene expression data
- microarray data analysis
- microarray data
- clustering algorithm
- gene regulation
- biological processes
- gene expression patterns
- clustering method
- functional genomics
- high dimensionality
- drosophila melanogaster
- clustering analysis
- dna microarray
- machine learning
- biological networks
- binding sites
- non stationary
- colon cancer
- document clustering
- data points
- analysis of gene expression
- genomic data
- regulatory networks
- k means
- cluster ensemble
- high dimensional
- gene expression data sets
- microarray datasets
- gene interactions
- self organizing maps
- cluster analysis
- differentially expressed genes
- biclustering algorithms
- unsupervised learning
- high throughput
- data sets