Conference Paper

Finding Similar Patterns in Microarray Data.

DOI: 10.1007/11589990_185 Conference: AI 2005: Advances in Artificial Intelligence, 18th Australian Joint Conference on Artificial Intelligence, Sydney, Australia, December 5-9, 2005, Proceedings
Source: DBLP


In this paper we propose a clustering algorithm called s- Cluster for analysis of gene expression data based on pattern-similarity. The algorithm captures the tight clusters exhibiting strong similar ex- pression patterns in Microarray data,and allows a high level of overlap among discovered clusters without completely grouping all genes like other algorithms. This reflects the biological fact that not all functions are turned on in an experiment, and that many genes are co-expressed in multiple groups in response to different stimuli. The experiments have demonstrated that the proposed algorithm successfully groups the genes with strong similar expression patterns and that the found clusters are interpretable.

Download full-text


Available from: Xiaodi Huang