Identification of coherent patterns in gene expression data using an efficient biclustering algorithm and parallel coordinate vi

Background: The DNA microarray technology allows the measurement of expression levels of thousands of genes under tens/hundreds of different conditions. In microarray data, genes with similar functions usually co-express under certain conditions only [1]. Thus, biclustering which clusters genes and conditions simultaneously is preferred over the traditional clustering technique in discovering these coherent genes. Various biclustering algorithms have been developed using different bicluster formulations. Unfortunately, many useful formulations result in NP-complete problems. In this article, we investigate an efficient method for identifying a popular type of biclusters called additive model. Furthermore, parallel coordinate (PC) plots are used for bicluster visualization and analysis. Results: We develop a novel and efficient biclustering algorithm which can be regarded as a greedy version of an existing algorithm known as pCluster algorithm. By relaxing the constraint in homogeneity...

• Type: Journal
• Year: 2008
• Where: BMCBI
• Authors: Kin-On Cheng, Ngai-Fong Law, Wan-Chi Siu, Alan Wee-Chung Liew
• Keywords: Algorithm, Biclustering Algorithm, BMCBI 2008, PCluster Algorithm