A cube framework for incorporating inter-gene information into biological data mining

Kuan Ming Lin, Jaewoo Kang, Hanjun Shin, Jusang Lee

    Research output: Contribution to journalArticlepeer-review

    4 Citations (Scopus)

    Abstract

    Large volumes of microarray data are registered daily in public repositories such as SMD (Belkin and Niyogi, 2003) and GEO (Ashburner et al., 2000). Such repositories have quickly become a community resource. However, due to the inherent heterogeneity of the microarray experiments, the data generated from different experiments could not be directly integrated and hence the resources have not been fully utilised. To address this problem, we propose a new microarray integration framework that achieves high-quality integration through exploiting invariant features such as relative information among genes. We also show how the proposed approach generalises the previous frameworks.

    Original languageEnglish
    Pages (from-to)3-22
    Number of pages20
    JournalInternational Journal of Data Mining and Bioinformatics
    Volume3
    Issue number1
    DOIs
    Publication statusPublished - 2009

    Keywords

    • Bioinformatics
    • Cube framework
    • Data mining
    • Intergene analysis
    • Second-order correlation
    • TSP

    ASJC Scopus subject areas

    • Information Systems
    • Biochemistry, Genetics and Molecular Biology(all)
    • Library and Information Sciences

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