Microarray data

Prediction of core cancer genes using a hybrid of feature selection and machine learning methods

Y. X. Liu, Zhang, N. N., He, Y., and Lun, L. J., 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.

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