Association between expression of random gene sets and survival is evident in multiple cancer types and may be explained by sub-classification.
Yishai ShimoniPublished in: PLoS Comput. Biol. (2018)
Keyphrases
- gene sets
- fold cross validation
- microarray data
- cancer classification
- cancer datasets
- microarray
- gene selection
- classification accuracy
- microarray datasets
- statistical significance
- differential expression
- logistic regression
- text classification
- feature selection
- machine learning methods
- decision trees
- breast cancer
- gene expression
- support vector machine svm
- unsupervised learning
- gene expression profiles
- high dimensionality
- classification models
- genome wide
- text mining
- feature vectors
- support vector
- machine learning