JOURNAL OF COMPUTERS (JCP)
ISSN : 1796-203X
Volume : 3    Issue : 10    Date : October 2008

A Parallel Algorithm for Gene Expressing Data Biclustering
Wei Liu and Ling Chen
Page(s): 71-77
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Abstract
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. A parallel biclustering algorithm
for gene expressing data 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 all the 2*2
submatrices of the gene expressing 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
over other similar algorithms in terms of processing speedup and quality of clustering and efficiency.
Index Terms
bioinformatics, biclustering, gene expression data