Gene selection and disease prediction from gene expression data using a two-stage hetero-associative memory.
Laura Cleofas-SánchezJ. Salvador SánchezVicente GarcíaPublished in: Prog. Artif. Intell. (2019)
Keyphrases
- associative memory
- gene selection
- gene expression data
- dna microarray
- microarray
- microarray data
- cancer classification
- gene expression
- ovarian cancer
- relevant genes
- gene expression profiles
- gene expression datasets
- cancer diagnosis
- gene expression data analysis
- feature selection
- dna microarray data
- gene sets
- data sets
- gene expression data sets
- informative genes
- expression profiles
- tumor classification
- gene regulatory networks
- microarray datasets
- gene expression analysis
- biological knowledge
- neural network
- gene networks
- microarray data analysis
- high throughput
- regulatory networks
- feature ranking
- biologically relevant
- high dimensionality
- kernel methods
- colon cancer
- support vector machine svm
- neural network model
- molecular biology
- gene expression patterns
- high dimensional data
- machine learning
- data mining
- gene ontology
- selected genes