Prediction of core cancer genes using a hybrid of feature selection and machine learning methods
“Prediction of core cancer genes using a hybrid of feature selection and machine learning methods”, vol. 14, pp. 8871-8882, 2015.
, Machine learning techniques are of great importance in the analysis of microarray expression data, and provide a systematic and promising way to predict core cancer genes. In this study, a hybrid strategy was introduced based on machine learning techniques to select a small set of informative genes, which will lead to improving classification accuracy. First feature filtering algorithms were applied to select a set of top-ranked genes, and then hierarchical clustering and collapsing dense clusters were used to select core cancer genes.