A Parallel Biclustering Algorithm for Gene Expressing Data

Biclustering the gene expressing data is an important task in bioinformatics. A parallel biclustering algorithm for gene expressing data is presented. The algorithm starts from the data sets containing pair of rows and columns of the data matrix, and gets the biclusters by gradually adding columns and rows on the data sets. A pruning technique is also proposed to reduce computing time. Experimental results show that our algorithm has superiority to other similar algorithms in terms of processing speed and quality of clustering.