ICGA-PSO-ELM Approach for Accurate Multiclass Cancer Classification Resulting in Reduced Gene Sets in Which Genes Encoding Secreted Proteins Are Highly Represented.
Saras SaraswathiSuresh SundaramNarasimhan SundararajanMichael T. ZimmermannMarit Nilsen-HamiltonPublished in: IEEE ACM Trans. Comput. Biol. Bioinform. (2011)
Keyphrases
- multi class
- cancer classification
- gene sets
- microarray data
- gene ontology
- gene selection
- microarray
- feature selection
- gene expression data
- informative genes
- random forest
- support vector machine
- biological processes
- pairwise
- protein protein interactions
- gene expression profiles
- microarray datasets
- gene expression
- statistical significance
- fold cross validation
- base classifiers
- cost sensitive
- data sets
- experimental conditions
- protein sequences
- gene expression analysis
- computational methods
- protein interaction
- feature ranking
- semantic similarity
- high dimensional
- data mining