title: Signal Partitioning Algorithm for Highly Efficient Gaussian Mixture Modeling in Mass Spectrometry.
abstract: Mixture - modeling of mass spectra is an approach with many potential applications including peak detection and quantification, smoothing, de-noising, feature extraction and spectral signal compression. However, existing algorithms do not allow for automated analyses of whole spectra. Therefore, despite highlighting potential advantages of mixture modeling of mass spectra of peptide/protein mixtures and some preliminary results presented in several papers, the mixture modeling approach was so far not developed to the stage enabling systematic comparisons with existing software packages for proteomic mass spectra analyses. In this paper we present an efficient algorithm for Gaussian mixture modeling of proteomic mass spectra of different types (e.g., MALDI-ToF profiling, MALDI-IMS). The main idea is automated partitioning of protein mass spectral signal into fragments. The obtained fragments are separately decomposed into Gaussian mixture models. The parameters of the mixture models of fragments are then aggregated to form the mixture model of the whole spectrum. We compare the elaborated algorithm to existing algorithms for peak detection and we demonstrate improvements of peak detection efficiency obtained by using Gaussian mixture modeling. We also show applications of the elaborated algorithm to real proteomic datasets of low and high resolution.
authors.affiliation: Institute of Informatics, Silesian University of Technology, Gliwice, Poland.
authors.forename: Andrzej
authors.initials: A
authors.lastname: Polanski
authors.affiliation: Institute of Automatic Control, Silesian University of Technology, Gliwice, Poland.
authors.forename: Michal
authors.initials: M
authors.lastname: Marczyk
authors.affiliation: Maria Sklodowska-Curie Memorial Cancer Center and Institute of Oncology, Gliwice, Poland.
authors.forename: Monika
authors.initials: M
authors.lastname: Pietrowska
authors.affiliation: Maria Sklodowska-Curie Memorial Cancer Center and Institute of Oncology, Gliwice, Poland.
authors.forename: Piotr
authors.initials: P
authors.lastname: Widlak
authors.affiliation: Institute of Automatic Control, Silesian University of Technology, Gliwice, Poland.
authors.forename: Joanna
authors.initials: J
authors.lastname: Polanska
mesh_terms: D000465:Algorithms; D040901:Proteomics; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization / Q000379:methods*