Deep learning-based classification and interpretation of gene expression data from cancer and normal tissues.
TaeJin AhnTaewan GooChan-hee LeeSungmin KimKyullhee HanSangick ParkTaesung ParkPublished in: Int. J. Data Min. Bioinform. (2020)
Keyphrases
- gene expression data
- tissue samples
- deep learning
- cancer classification
- cancer diagnosis
- colon cancer
- gene expression profiles
- dna microarray
- microarray
- cancer datasets
- gene expression
- gene selection
- gene expression datasets
- gene expression analysis
- gene expression data sets
- microarray data
- gene expression data analysis
- high dimensionality
- feature selection
- gene expression microarray data
- tumor classification
- unsupervised learning
- cell nuclei
- analysis of gene expression data
- decision trees
- random forest
- high throughput
- microarray datasets
- data sets
- high dimensional data
- high dimensional
- feature vectors
- gene expression patterns
- pattern recognition
- normal tissue
- machine learning
- weakly supervised
- supervised learning
- feature space
- neural network