Maximal Subspace Coregulated Gene Clustering

Clustering is a popular technique for analyzing microarray data sets, with n genes and m experimental conditions. As explored by biologists, there is a real need to identify coregulated gene clusters, which include both positive and negative regulated gene clusters. The existing pattern-based and te...

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Bibliographic Details
Published in:IEEE transactions on knowledge and data engineering 2008-01, Vol.20 (1), p.83-98
Main Authors: Yuhai Zhao, Yu, J.X., Guoren Wang, Lei Chen, Bin Wang, Ge Yu
Format: Article
Language:English
Subjects:
Algorithms
and association rules
Applied sciences
Biological and medical sciences
Biological information theory
Biologists
classification
Clustering
Clustering algorithms
Clusters
Coding
Computer science
control theory
systems
Computer Society
Data analysis
Data mining
Data processing. List processing. Character string processing
Exact sciences and technology
Fundamental and applied biological sciences. Psychology
Fungi
Gene expression
Genes
Memory organisation. Data processing
Molecular and cellular biology
Molecular genetics
Proteins
Software
Studies
Subspace constraints
Subspaces
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Summary:Clustering is a popular technique for analyzing microarray data sets, with n genes and m experimental conditions. As explored by biologists, there is a real need to identify coregulated gene clusters, which include both positive and negative regulated gene clusters. The existing pattern-based and tendency-based clustering approaches cannot directly be applied to find such coregulated gene clusters, because they are designed for finding positive regulated gene clusters. In this paper, in order to cluster coregulated genes, we propose a coding scheme that allows us to cluster two genes into the same cluster if they have the same code, where two genes that have the same code can be either positive or negative regulated. Based on the coding scheme, we propose a new algorithm for finding maximal subspace coregulated gene clusters with new pruning techniques. A maximal subspace coregulated gene cluster clusters a set of genes on a condition sequence such that the cluster is not included in any other subspace coregulated gene clusters. We conduct extensive experimental studies. Our approach can effectively and efficiently find maximal subspace coregulated gene clusters. In addition, our approach outperforms the existing approaches for finding positive regulated gene clusters.
ISSN:1041-4347
1558-2191
DOI:10.1109/TKDE.2007.190670