Animated Oat Optimization Algorithm for Gene Selection

Gene selection is an important research content in bioinformatics and pattern recognition. Genetic data has the nature of small sample size and high dimension. Only a small number of genes associated with tumorigenesis can serve as biomarkers. This study proposes a new hybrid gene feature selection method, mutation Animated Oat Optimization Algorithm (mAOO). First, the genes are evaluated through the t-test algorithm to select the important genes. Then, Animated Oat Optimization Algorithm (AOO) combined with mutation operator in genetic algorithm is used to select important genes. Experimental results show that the performance of the proposed algorithm on gene expression datasets is superior to other popular algorithms in most cases.