Latest microarray technique can measure the expression levels of thousands of genes under a set of conditions, and generates some large-scale microarray datasets. Biclustering can perform clustering of rows and columns of those dataset simultaneously, allowing the mining of additional information from microarray datasets which is important in bioinformatics research and biomedical applications. Since the biclustering problem is combinatorial, and multi-objective ant optimization systems present several advantages during dealing with this kind of problem. This paper proposes a novel multi-objective ant colony optimization biclustering algorithm to mine biclusters from microarray dataset. Experimental results on real dataset show that our approach can find significant biclusters of high quality.