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https://hdl.handle.net/1959.11/4568
Title: | Finding Similar Patterns in Microarray Data | Contributor(s): | Chen, Xiangsheng (author); Li, Jiuyong (author); Daggard, Grant (author); Huang, Xiaodi (author) | Publication Date: | 2005 | Handle Link: | https://hdl.handle.net/1959.11/4568 | Abstract: | 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 expression 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. | Publication Type: | Conference Publication | Conference Details: | AI 2005: 18th Australian Joint Conference on Artificial Intelligence, Sydney, Australia, 5th - 9th December, 2005 | Source of Publication: | Al 2005: Advances in Artificial Intelligence, p. 1272-1276 | Publisher: | Springer | Place of Publication: | Berlin, Germany | Fields of Research (FoR) 2008: | 080109 Pattern Recognition and Data Mining | Socio-Economic Objective (SEO) 2008: | 890205 Information Processing Services (incl. Data Entry and Capture) | Peer Reviewed: | Yes | HERDC Category Description: | E1 Refereed Scholarly Conference Publication | Publisher/associated links: | http://www.cis.unisa.edu.au/~lijy/AI05Final.pdf http://trove.nla.gov.au/work/20851994 |
Series Name: | Lecture Notes in Computer Science | Series Number : | 3809 |
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Appears in Collections: | Conference Publication |
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