Independent component analysis (ICA) is a statistical method applied to gene cluttering.Estimative separation matrix algorithm of ICA uses mainly Random Gradient Algorithm or Natural Gradient Algorithm.And yet these algorithms can only get the partial optimized solution.This paper proposes a new algorithm of gene clustering based on genetic algorithm.The key idea is by using genetic algorithm instead of previous estimative separation matrix algorithms in ICA to classify gene expression data.The former has an advantage of overcoming partial optimized solution.The analysis and experiments support our conclusion that gene clustering based on genetic algorithm has better performance.