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Abstract
Raman spectroscopy using feature selection schemes has considerable advantages over gas chromatography for the analysis of fatty acids' composition changes. Here, we introduce an educational methodology to demonstrate the potential of micro-Raman spectroscopy to determine with high accuracy the unsaturation or saturation degrees and composition changes of the fatty acids found in the lipid droplets of the LNCaP prostate cancer cells that were treated with various fatty acids. The methodology uses highly discriminatory wavenumbers among fatty acids present in the sample selected by using the Support Vector Machine algorithm.
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