Sorting of Single Biomolecules based on Fourier Polar Representation of Surface Enhanced Raman Spectra.
Fiche publication
Date publication
février 2016
Journal
Scientific reports
Auteurs
Membres identifiés du Cancéropôle Est :
Pr FINOT Eric
Tous les auteurs :
Leray A, Brulé T, Buret M, Colas des Francs G, Bouhelier A, Dereux A, Finot E
Lien Pubmed
Résumé
Surface enhanced Raman scattering (SERS) spectroscopy becomes increasingly used in biosensors for its capacity to detect and identify single molecules. In practice, a large number of SERS spectra are acquired and reliable ranking methods are thus essential for analysing all these data. Supervised classification strategies, which are the most effective methods, are usually applied but they require pre-determined models or classes. In this work, we propose to sort SERS spectra in unknown groups with an alternative strategy called Fourier polar representation. This non-fitting method based on simple Fourier sine and cosine transforms produces a fast and graphical representation for sorting SERS spectra with quantitative information. The reliability of this method was first investigated theoretically and numerically. Then, its performances were tested on two concrete biological examples: first with single amino-acid molecule (cysteine) and then with a mixture of three distinct odorous molecules. The benefits of this Fourier polar representation were highlighted and compared to the well-established statistical principal component analysis method.
Mots clés
Algorithms, Biosensing Techniques, Cysteine, chemistry, Models, Theoretical, Monte Carlo Method, Odorants, analysis, Spectrum Analysis, Raman, methods
Référence
Sci Rep. 2016 Feb;6:20383