On mining micro-array data by order-preserving submatrix

Lin Cheung*, David W. Cheung, Ben Kao, Kevin Y. Yip, Kwok Po NG

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

21 Citations (Scopus)


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 • 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.

Original languageEnglish
Pages (from-to)42-64
Number of pages23
JournalInternational Journal of Bioinformatics Research and Applications
Issue number1
Publication statusPublished - 2007

Scopus Subject Areas

  • Biomedical Engineering
  • Health Informatics
  • Clinical Biochemistry
  • Health Information Management

User-Defined Keywords

  • Bioinformatics
  • Data mining
  • Gene expression
  • OPSM
  • Order-Preserving Submatrix
  • Pattern-based clustering


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