MRCluster: Mining Constant Row Bicluster in Gene Expression Data
Biclustering is one of the important techniques for gene expression data analysis. A bicluster is a set of genes coherently expressed for a set of biological conditions. Various biclustering algorithms have been proposed to find biclusters of different types. However, most of them are not efficient. We propose a novel algorithm MRCluster to mine constant row biclusters from real-valued dataset. MRCluster uses Apriori property and several novel pruning techniques to mine biclusters efficiently. We compare our algorithm with a recent approach RAP, and experimental results show that MRCluster is much more efficient than RAP in mining biclusters with constant rows from real-valued gene expression data.
Robin G. Qiu and Yongfeng Ju
M. Miao et al., "MRCluster: Mining Constant Row Bicluster in Gene Expression Data", Applied Mechanics and Materials, Vols. 135-136, pp. 628-633, 2012