A simple approach to normalization for spectroscopic data mining

Paul D. Dobson, Andrew J. Doig, Ewan W. Blanch

    Research output: Contribution to journalArticlepeer-review


    Different approaches to normalization for spectroscopic data mining are discussed. A widely used approach to spectra normalization is to adjust all data to a region of known intensity. Statistical approaches to normalization are based on calculating some property of the spectrum that relates to the magnitude of the intensity stretch. Optical spectroscopic techniques, including Fourier transform infrared (FT-IR) and ultraviolet circular dichroism (UVCD), are useful for studying biological molecules, as they are more widely applicable than the high-resolution method of X-ray crystallography. Databases of protein spectra are currently being developed using these spectroscopic techniques for fold recognition and structural quantification.
    Original languageEnglish
    Pages (from-to)542-544
    Number of pages2
    JournalApplied Spectroscopy
    Issue number4
    Publication statusPublished - Apr 2005


    • Data mining
    • Intensity stretch
    • Normalization
    • Scale canceling
    • Standards


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