Parallel identification of gene biclusters with coherent evolutions

Finding clusters of genes with expression levels that evolve coherently under subsets of conditions can help uncover genetic pathways. This can be done by applying a biclustering procedure to gene expression data. Given a microarray data set with M genes and N conditions, we define a bicluster with...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on signal processing 2006-06, Vol.54 (6), p.2408-2417
Main Authors: Tewfik, A.H., Tchagang, A.B., Vertatschitsch, L.
Format: Article
Language:English
Subjects:
Biclustering
Bioinformatics
Biomedical engineering
clustering
Clustering algorithms
Data analysis
Diseases
Displays
Evolution (biology)
gene coregulation
Gene expression
Genetics
Mathematics
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Finding clusters of genes with expression levels that evolve coherently under subsets of conditions can help uncover genetic pathways. This can be done by applying a biclustering procedure to gene expression data. Given a microarray data set with M genes and N conditions, we define a bicluster with coherent evolution as a subset of genes with expression levels that are nondecreasing as a function of a particular ordered subset of conditions. We propose a new biclustering procedure that identifies all biclusters with a specified number of K conditions in parallel with O(MK) complexity. Unlike almost all prior biclustering techniques, the proposed approach is guaranteed to find all biclusters with a specified minimum numbers of genes and conditions in the data set. All of the biclusters it identifies have no imperfection, i.e., the evolutions of the genes in each bicluster will be coherent across all conditions in the bicluster. Furthermore, the complexity of the proposed approach is lower than that of prior approaches.
ISSN:1053-587X
1941-0476
DOI:10.1109/TSP.2006.873720