Article Abstract

	Title:	On mining micro-array data by Order-Preserving Submatrix
	Author:	Lin Cheung, David W. Cheung, Ben Kao, Kevin Y. Yip, Michael K. Ng
	Address:	Department of Computer Science, University of Hong Kong, Hong Kong. ' Department of Computer Science, University of Hong Kong, Hong Kong. ' Department of Computer Science, University of Hong Kong, Hong Kong. ' Department of Computer Science, Yale University, USA. ' Department of Mathematics, Hong Kong Baptist University, Hong Kong
	Journal:	International Journal of Bioinformatics Research and Applications 2007 - Vol. 3, No.1  pp. 42 - 64
	Abstract:	We study the problem of pattern-based subspace clustering which is clustering by pattern similarity finds objects that exhibit a coherent pattern of rises and falls in subspaces. Applications of pattern-based subspace clustering include DNA micro-array data analysis. Our goal is to devise pattern-based clustering methods that are capable of: discovering useful patterns of various shapes, and discovering all significant patterns. Our approach is to extend the idea of Order-Preserving Submatrix (OPSM). We devise a novel algorithm for mining OPSM, show that OPSM can be generalised to cover most existing pattern-based clustering models and propose a number of extensions to the original OPSM model.
	Keywords:	gene expression; data mining; pattern-based clustering; order-preserving submatrix; OPSM; bioinformatics; biomedical data; biomedical engineering; DNA micro-array data; subspace clustering; pattern similarity.
	DOI:	10.1504/IJBRA.2007.011834
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