Boosting for feature selection for microarray data analysis

We have investigated the use of boosting techniques for feature selection for microarray data analysis. We propose a novel algorithm for feature selection and have tested it on three datasets. The results clearly show that our boosting technique for feature selection outperformed the Wilcoxon-Mann-Whitney U-test commonly used in microarray data analysis, and produced more accurate boosting ensembles when they were constructed with the features selected by our technique.