Mining Order-Preserving Submatrices from Data with Repeated Measurements
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AbstractOrder-preserving submatrices (OPSM's) have been shown useful in capturing concurrent patterns in data when the relative magnitudes of data items are more important than their exact values. For instance, in analyzing gene expression profiles obtained from microarray experiments, the relative magnitudes are important both because they represent the change of gene activities across the experiments, and because there is typically a high level of noise in data that makes the exact values untrustable. To cope with data noise, repeated experiments are often conducted to collect multiple measurements. We propose and study a more robust version of OPSM, where each data item is represented by a set of values obtained from replicated experiments. We call the new problem OPSM-RM (OPSM with repeated measurements). We define OPSM-RM based on a number of practical requirements. We discuss the computational challenges of OPSM-RM and propose a generic mining algorithm. We further propose a series of techniques to speed up two time dominating components of the algorithm. We show the effectiveness and efficiency of our methods through a series of experiments conducted on real microarray data.
All Author(s) ListYip KY, Kao B, Zhu XJ, Chui CK, Lee SD, Cheung DW
Journal nameIEEE Transactions on Knowledge and Data Engineering
Detailed descriptionTo ORKTS: I am the first author of the publication.

2012 ISI journal impact factor: 1.892
Volume Number25
Issue Number7
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1587 - 1600
LanguagesEnglish-United Kingdom
Keywordsbioinformatics; Data mining; mining methods and algorithms
Web of Science Subject CategoriesComputer Science; Computer Science, Artificial Intelligence; COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE; Computer Science, Information Systems; COMPUTER SCIENCE, INFORMATION SYSTEMS; Engineering; Engineering, Electrical & Electronic; ENGINEERING, ELECTRICAL & ELECTRONIC

Last updated on 2020-17-09 at 01:41