Title: On mining micro-array data by Order-Preserving Submatrix

Authors: Lin Cheung, David W. Cheung, Ben Kao, Kevin Y. Yip, Michael K. Ng

Addresses: 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

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

International Journal of Bioinformatics Research and Applications, 2007 Vol.3 No.1, pp.42 - 64

Published online: 26 Dec 2006 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article