On biclustering of gene expression data

Abstract

The problem of finding groups of co-regulated genes is considered one of the major challenges in the analysis of gene expression data. Biclustering may be considered as one of the main techniques to analyze these data. Biclustering is a non-supervised technique outperforms the traditional clustering techniques because it can group both genes and conditions in the same time. A gene or condition may belong to more than one bicluster and hence to more than biological function or process. In this survey, we introduced some definitions of the biclustering with its mathematical model after that we reviewed some biclustering techniques based on the type of biclusters they can find; finally a set of validation measures were introduced to validate the biclustering techniques emphasizing the biological measures.