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

58 Scopus citations

Abstract

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
Volume98
Issue number6
DOIs
StatePublished - Mar 25 2008

All Science Journal Classification (ASJC) codes

  • Oncology
  • Cancer Research

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