Abstract
Techniques are presented to develop spectroscopic factors directly from circular dichroism spectra of proteins using singular value decomposition on a small database. Four spectra of maximum spectral variability are chosen to characterize the database. These selected protein spectra are then factored by singular values into component spectra, which are collected as comparative vector characteristics used as factor fractions. The necessary standardization for comparison is achieved using unit normalized spectra. Those spectra are used to quantify the parameter uncertainties as a means for comparison. The difference between the fit spectrum and the data spectrum for each protein is analyzed by least square to obtain parameter uncertainties due to the model. The sum of the factor fractions over the database is within the theoretical predictions.
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