1997
DOI: 10.1038/nm0897-927
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A new structural analysis of DNA using statistical models of infrared spectra

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Cited by 20 publications
(37 citation statements)
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“…In an attempt to answer this question, we used Fourier transform-infrared (FT-IR) spectroscopy with multivariate statistics to delineate structural differences between thin films of a 25-base DNA strand and comparable strands containing centrally located single G o and A o groups. FT-IR͞statistical analysis was previously used to study subtle changes in base and phospho-deoxyribose structures of DNA in relation to tumor progression (13)(14)(15)(16)(17)(18)(19). In the present study, a number of spectral differences attributable to base interactions and backbone conformations were identified between the 25-base parent strand and derivatives containing G o and A o substituents.…”
mentioning
confidence: 73%
“…In an attempt to answer this question, we used Fourier transform-infrared (FT-IR) spectroscopy with multivariate statistics to delineate structural differences between thin films of a 25-base DNA strand and comparable strands containing centrally located single G o and A o groups. FT-IR͞statistical analysis was previously used to study subtle changes in base and phospho-deoxyribose structures of DNA in relation to tumor progression (13)(14)(15)(16)(17)(18)(19). In the present study, a number of spectral differences attributable to base interactions and backbone conformations were identified between the 25-base parent strand and derivatives containing G o and A o substituents.…”
mentioning
confidence: 73%
“…A t test was performed at each wavenumber to determine the statistical differences (P values) between DNA groups (1,2,14). Principal components analysis (6,15), which involves Ϸ10 6 correlations between spectral absorbances, integrates different properties of the spectra, such as changes in peak heights and peak locations.…”
Section: Methodsmentioning
confidence: 99%
“…Principal components analysis (6,15), which involves Ϸ10 6 correlations between spectral absorbances, integrates different properties of the spectra, such as changes in peak heights and peak locations. This analysis resulted in 10 principal component (PC) scores per sample (1,2,14). A t test established statistical differences between groups for each PC score.…”
Section: Methodsmentioning
confidence: 99%
“…PCs analysis was performed on the mean spectrum of each sample, resulting in 10 PC scores per sample (22,23). Significant differences in the PC scores between tissue groups were determined by using t tests (Table 1).…”
Section: Gc-msmentioning
confidence: 99%
“…PCs with significant differences (P Ͻ 0.05) were used to construct two-dimensional scatter plots. The separation of sample clusters in the plots signifies that the groups are structurally dissimilar (15,22). Significant differences (P Ͻ 0.05) in PCs of primary prostate tumors and metastasizing primary tumors were used in logistic regression analysis to predict the probability of metastatic cancer, and the sensitivity and specificity of prediction were calculated.…”
Section: Gc-msmentioning
confidence: 99%