Microarray Gene Selection and Cancer Classification Method Using Artificial Bee Colony and SVM Algorithms (ABC-SVM)

Abstract

Despite the considerable efforts that are done for Microarray gene expression profile, biomarker discovery or gene selection process remains a complex challenge for biologists and computer scientists. This article presented an Artificial Bee Colony (ABC) based approach for accurate classification of cancer microarray data using support vector machine (SVM) as a classifier. The approach is able to deal with the high dimensionality of the microarray data. According to literature for microarray data analysis, up to our knowledge, this is the first attempt to apply Artificial Bee Colony based algorithm as gene selection method for cancer classification problem using Microarray gene expression profile. Comparing with other algorithms that are proposed in the literature, we can conclude that our proposed algorithm (ABC-SVM) obtains promising results for gene selection and cancer classification problems.