Journal
EXPERT REVIEW OF PROTEOMICS
Volume 2, Issue 6, Pages 847-862Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1586/14789450.2.6.847
Keywords
biomarker discovery; clinical proteomics; clinical statistics; data analysis; expression profiling; mass spectrometry; pattern recognition; time-of-flight mass spectrometry
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Protein expression profiling is increasingly being used to discover, validate and characterize biomarkers that can potentially be used for diagnostic purposes and to aid in pharmaceutical development. Correct analysis of data obtained from these experiments requires an understanding of the underlying analytic procedures used to obtain the data, statistical principles underlying high-dimensional data and clinical statistical tools used to determine the utility of the interpreted data. This review summarizes each of these steps, with the goal of providing the nonstatistician proteomics researcher with a working understanding of the various approaches that may be used by statisticians. Emphasis is placed on the process of mining high-dimensional data to identify a specific set of biomarkers that may be used in a diagnostic or other assay setting.
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