title: A review of blind source separation in NMR spectroscopy.
abstract: Fourier transform is the data processing naturally associated to most NMR experiments. Notable exceptions are Pulse Field Gradient and relaxation analysis, the structure of which is only partially suitable for FT. With the revamp of NMR of complex mixtures, fueled by analytical challenges such as metabolomics, alternative and more apt mathematical methods for data processing have been sought, with the aim of decomposing the NMR signal into simpler bits. Blind source separation is a very broad definition regrouping several classes of mathematical methods for complex signal decomposition that use no hypothesis on the form of the data. Developed outside NMR, these algorithms have been increasingly tested on spectra of mixtures. In this review, we shall provide an historical overview of the application of blind source separation methodologies to NMR, including methods specifically designed for the specificity of this spectroscopy.
authors.affiliation: Aix Marseille Université, Centrale Marseille, CNRS, iSm2 UMR 7313, 13397 Marseille, France.
authors.forename: Ichrak
authors.initials: I
authors.lastname: Toumi
authors.affiliation: Aix Marseille Université, Centrale Marseille, CNRS, iSm2 UMR 7313, 13397 Marseille, France. Electronic address: s.caldarelli@univ-amu.fr.
authors.forename: Stefano
authors.initials: S
authors.lastname: Caldarelli
authors.affiliation: Aix-Marseille Université, CNRS, Centrale Marseille I2M, UMR 7373, 13453 Marseille, France.
authors.forename: Bruno
authors.initials: B
authors.lastname: Torrésani
mesh_terms: D000465:Algorithms; D000818:Animals; D045424:Complex Mixtures / Q000032:analysis*; D006801:Humans; D019906:Nuclear Magnetic Resonance, Biomolecular / Q000379:methods*; D012815:Signal Processing, Computer-Assisted; D012984:Software
chemical_list: D045424:Complex Mixtures
keywords: BSS; Independent component analysis; NMR spectroscopy; Non negative matrix factorization; Sparsity