Approaches to working in high-dimensional data spaces: Gene expression microarrays

Y. Wang, D. J. Miller, R. Clarke

    Research output: Contribution to journalShort surveypeer-review

    44 Scopus citations


    This review provides a focused summary of the implications of high-dimensional data spaces produced by gene expression microarrays for building better models of cancer diagnosis, prognosis, and therapeutics. We identify the unique challenges posed by high dimensionality to highlight methodological problems and discuss recent methods in predictive classification, unsupervised subclass discovery, and marker identification.

    Original languageEnglish (US)
    Pages (from-to)1023-1028
    Number of pages6
    JournalBritish Journal of Cancer
    Issue number6
    StatePublished - Mar 25 2008

    All Science Journal Classification (ASJC) codes

    • Oncology
    • Cancer Research

    Fingerprint Dive into the research topics of 'Approaches to working in high-dimensional data spaces: Gene expression microarrays'. Together they form a unique fingerprint.

    Cite this