Parallel Biclustering Algorithm for Gene Expressing Data
Ling Chen · Journal of Chinese Computer Systems · 2009
Biclustering of the gene expressing data is an important task in bioinformatics.By clustering the gene expressing data obtained under different experimental conditions,function and regulatory elements of the gene sequence can be analyzed and recognized.After studying the problem of gene expressing data analysis,a parallel biclustering algorithm is presented.Based on the anti-monotones property of the quality of the data sets with their sizes,the algorithm starts from the data sets containing of every two rows and every two columns of the data matrix,and gets the final biclusters by gradually adding columns and rows on the data sets.Experimental results show that our algorithm has superiority our other similar algorithms in terms of processing speed and quality of clustering and efficiency.