MSR-based algorithms for biclustering of microarray gene expression data

Biclustering plays a vital role in the analysis of gene expression data. The biclustering technique was proposed in the year 2000. For the past two decades, several biclustering methods and applications have been used to improve the quality to make sense of large microarray datasets. To find a highly correlated set of genes under specific conditions, usually one uses a measure or cost function. In such cases, it does not indicate that biclustering methods base their search on evaluation measures to identify the coherent biclusters. However, there is a substantial deviation between exploration in biclustering techniques and qualitative measure. Here, we present a review of different biclustering methods with the use of the most efficient measure called mean square residue within the search method. This review will guide researchers to fruitfully investigate their large microarray gene expression data and give meaningful, novel insights with greater efficiency.