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Biclustering of Gene Expression Data Based on Local Nearness
In EGC 2006, vol. RNTI-E-6, pp.681-692
The analysis of gene expression data in DNA chips is an important
tool used in genomic research whose main objectives range from the study of
the functionality of specific genes and their participation in biological process
to the reconstruction of diseases's conditions and their subsequent prognosis.
Gene expression data are arranged in matrices where each gene corresponds to
one row and every column represents one specific experimental condition. The
biclustering techniques have the purpose of finding subsets of genes that show
similar activity patterns under a subset of conditions. Our approach consists of
a biclustering algorithm based on local nearness. The algorithm searches for
biclusters in a greedy fashion, starting with two–genes biclusters and including
as much as possible depending on a distance threshold which guarantees the
similarity of gene behaviors.