Machine Learning Classification and Structure-Functional Analysis of Cancer Mutations Reveal Unique Dynamic and Network Signatures of Driver Sites in Oncogenes and Tumor Suppressor Genes.
Steve AgajanianOluyemi OdeyemiNathaniel BischoffSimrath RatraGennady M. VerkhivkerPublished in: J. Chem. Inf. Model. (2018)
Keyphrases
- machine learning
- cancer diagnosis
- functional analysis
- tissue samples
- gene selection
- tumor classification
- gene expression profiles
- cancer classification
- colon cancer
- network structure
- machine learning methods
- dna microarray
- feature selection
- breast cancer
- gene expression data
- cancer datasets
- decision trees
- microarray
- support vector machine
- microarray data
- lung cancer
- gene expression
- text classification
- supervised learning
- machine learning algorithms
- gene expression datasets
- ovarian cancer
- informative genes
- learning algorithm
- gene expression analysis
- gene networks
- gene expression data sets
- roc analysis
- normal tissue
- network model
- support vector machine svm
- structural motifs
- cell lines
- text mining
- candidate genes