TY - JOUR

T1 - Biospectroscopy to metabolically profile biomolecular structure

T2 - a multistage approach linking computational analysis with biomarkers

AU - Kerns, Jemma

AU - Trevisan, Julio

AU - Scott, A. D.

AU - Carmichael, P. L.

AU - Pollock, Hubert M.

AU - Martin-Hirsch, P. L.

AU - Martin, Frank L.

PY - 2011

Y1 - 2011

N2 - Biospectroscopy is employed to derive absorbance spectra representative of biomolecules present in biological samples. The mid-infrared region (λ = 2.5 μm – 25μm) is absorbed to give a biochemical-cell fingerprint (ṽ = 1800 cm-1 – 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, prediction and mechanistic of cellular behaviour. Biospectroscopy is a high-throughput non-invasive 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.

AB - Biospectroscopy is employed to derive absorbance spectra representative of biomolecules present in biological samples. The mid-infrared region (λ = 2.5 μm – 25μm) is absorbed to give a biochemical-cell fingerprint (ṽ = 1800 cm-1 – 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, prediction and mechanistic of cellular behaviour. Biospectroscopy is a high-throughput non-invasive 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.

KW - Biological Markers

KW - Cluster Analysis

KW - Computational Biology

KW - Discriminant Analysis

KW - Least-Squares Analysis

KW - Molecular Structure

KW - Multivariate Analysis

KW - Principal Component Analysis

KW - Spectrum Analysis

U2 - 10.1021/pr101067u

DO - 10.1021/pr101067u

M3 - Journal article

C2 - 21210632

VL - 10

SP - 1437

EP - 1448

JO - Journal of Proteome Research

JF - Journal of Proteome Research

SN - 1535-3893

IS - 4

ER -