Compact cancer biomarkers discovery using a swarm intelligence feature selection algorithm

Biomarker discovery is a typical application from functional genomics Due to the large number of genes studied simultaneously in microarray data feature selection is a key step Swarm intelligence has emerged as a solution for the feature selection problem However swarm intelligence settings for feature selection fail to select small features subsets We have proposed a swarm intelligence feature selection algorithm based on the initialization and update of only a subset of particles in the swarm In this study we tested our algorithm in 11 microarray datasets for brain leukemia lung prostate and others We show that the proposed swarm intelligence algorithm successfully Increase the classification accuracy and decrease the number of selected features compared to other swarm intelligence methods (C) 2010 Elsevier Ltd All rights reserved