Biospectroscopy to metabolically profile biomolecular structure: a multistage approach linking computational analysis with biomarkers

Biospectroscopy is employed to derive absorbance spectra representative of biomolecules present in biological samples. The mid-infrared region (λ = 2.5 μm−25 μm) is absorbed to give a biochemical-cell fingerprint (ṽ = 1800−900 cm−1). Cellular material produces complex spectra due to the variety of...

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Published inJournal of proteome research Vol. 10; no. 4; pp. 1437 - 1448
Main Authors Kelly, Jemma G, Trevisan, Júlio, Scott, Andrew D, Carmichael, Paul L, Pollock, Hubert M, Martin-Hirsch, Pierre L, Martin, Francis L
Format Journal Article
LanguageEnglish
Published United States American Chemical Society 01.04.2011
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Summary:Biospectroscopy is employed to derive absorbance spectra representative of biomolecules present in biological samples. The mid-infrared region (λ = 2.5 μm−25 μm) is absorbed to give a biochemical-cell fingerprint (ṽ = 1800−900 cm−1). Cellular material produces complex spectra due to the variety of chemical bonds present. The complexity and size of spectral data sets warrant multivariate analysis for data reduction, interpretation, and classification. Various multivariate analyses are available including principal component analysis (PCA), partial least-squares (PLS), linear discriminant analysis (LDA), and evolving fuzzy rule-based classifier (eClass). Interpretation of both visual and numerical results facilitates biomarker identification, cell-type discrimination, and predictive and mechanistic understanding of cellular behavior. Biospectroscopy is a high-throughput nondestructive technology. A comparison of biomarkers/mechanistic knowledge determined from conventional approaches to biospectroscopy coupled with multivariate analysis often provides complementary answers and a novel approach for diagnosis of disease and cell biology.
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ISSN:1535-3893
1535-3907
DOI:10.1021/pr101067u