Biclustering of Gene Expression Data Using a Multi-objective Differential Evolution Algorithm
Cai Li · Journal of Chinese Computer Systems · 2010
Biclustering of the gene expression data has become a research focus in bioinformatics in recent years.Usually,the fluctuat consistency of gene expression activities and the volumn of biclusters are to be optimized at the same time when we solve the biclustering problem of gene expression data.However,it is difficult for a single-objective evolutionary biclustering algorithm to optimize these two objects at the same time.To address this issue,this paper employs a multi-objective differential evolution algorithm to solve the biclustering problem.The algorithm proposed in this paper was tested in real gene expression datasets.Experimental results show that the proposed algorithm has better clustering effect.