Abstract: Techniques for determining a microbial classification based on a mass spectrum are disclosed. A mass spectrometer generates a mass spectrum for a biological sample. A binning function is applied to the mass spectrum to generate a binned mass spectrum. As an example, a binned mass spectrum is associated with a set of bins having mass errors of the same value. A classification algorithm is applied to the binned mass spectrum to determine a microbial classification.

Abstract: A method for analyzing a multidimensional data set includes generating a multidimensional mass spectrometry data set from a sample; and generating an matrix representing the multidimensional mass spectrometry data set such that a first dimension and a second dimension of the multidimensional mass spectrometry data set correspond to a matrix cell location, and an ion intensity corresponds to a matrix cell value; and determining a class of the matrix from a plurality of matrix classes using a trained neural network matrix classifier.

Abstract: Techniques for determining a microbial classification based on a mass spectrum are disclosed. A mass spectrometer generates a mass spectrum for a biological sample. A binning function is applied to the mass spectrum to generate a binned mass spectrum. As an example, a binned mass spectrum is associated with a set of bins having mass errors of the same value. A classification algorithm is applied to the binned mass spectrum to determine a microbial classification.

Abstract: A method for analyzing a multidimensional data set includes generating a multidimensional mass spectrometry data set from a sample; and generating an matrix representing the multidimensional mass spectrometry data set such that a first dimension and a second dimension of the multidimensional mass spectrometry data set correspond to a matrix cell location, and an ion intensity corresponds to a matrix cell value; and determining a class of the matrix from a plurality of matrix classes using a trained neural network matrix classifier.

Abstract: A mass spectrometric analysis method comprises: (1) processing a mass spectrum to reduce the signals to monoisotopic values; (2) creating a list of differences between the monoisotopic values; (3) creating one or more lists of theoretical mass-to-charge differences among known adducts, charge states and polymerization states whose formation may be expected from various analyte molecules; (4) comparing the theoretical differences (line or edge in the network) to the list of differences from the mass spectrum and, where applicable, make and tabulate tentative species assignments; (5) assigning the mass spectral peaks to respective ion species in accordance with the redundancy of each assignment based on multiple independent calculated mass-to-charge differences pertaining to each peak; (6) choosing an ion species for further fragmentation or reaction in the mass spectrometer, based on the assigning; and (7) performing the fragmentation or reaction on the chosen ion species in the mass spectrometer.

Abstract: A mass spectrometric analysis method comprises: (1) processing a mass spectrum to reduce the signals to monoisotopic values; (2) creating a list of differences between the monoisotopic values; (3) creating one or more lists of theoretical mass-to-charge differences among known adducts, charge states and polymerization states whose formation may be expected from various analyte molecules; (4) comparing the theoretical differences (line or edge in the network) to the list of differences from the mass spectrum and, where applicable, make and tabulate tentative species assignments; (5) assigning the mass spectral peaks to respective ion species in accordance with the redundancy of each assignment based on multiple independent calculated mass-to-charge differences pertaining to each peak; (6) choosing an ion species for further fragmentation or reaction in the mass spectrometer, based on the assigning; and (7) performing the fragmentation or reaction on the chosen ion species in the mass spectrometer.

Abstract: A mass spectrometric analysis method comprises: (1) processing a mass spectrum to reduce the signals to monoisotopic values; (2) creating a list of differences between the monoisotopic values; (3) creating one or more lists of theoretical mass-to-charge differences among known adducts, charge states and polymerization states whose formation may be expected from various analyte molecules; (4) comparing the theoretical differences (line or edge in the network) to the list of differences from the mass spectrum and, where applicable, make and tabulate tentative species assignments; and (5) assigning the mass spectral peaks to respective ion species in accordance with the redundancy of each assignment based on multiple independent calculated mass-to-charge differences pertaining to each peak.

Abstract: A method for tandem mass spectrometry of a plurality of eluting compounds comprises: (a) performing, during a time period, the steps of: ionizing the plurality of eluting compounds to generate a plurality of precursor ion species; introducing the plurality of precursor ions into a fragmentation cell operated at constant fragmentation energy so as to generate a plurality of product-ion species from at least a portion of the precursor ion species; and generating a mass spectrum of the plurality of product-ion species; and (b) recognizing matches between certain of the product ion species generated during the time period based on correlations between elution profiles of the product ion species.

Abstract: Methods are disclosed for rapidly and reliably differentiating between ischemic and hemorrhagic stroke events in a human patient. The methods include obtaining a biological sample, such as blood serum, and analyzing the sample or a derivative thereof by mass spectrometry to measure the amount of one or more targeted proteins differentially present and ischemic and hemorrhagic stroke patients. The analysis may include proteolytic digestion of the biological sample and selective reaction monitoring (SRM) tandem mass spectrometry of the digested sample to determine the amounts of surrogate peptides corresponding to the targeted proteins.

Abstract: The present invention relates to biomarkers in maternal serum samples and methods for predicting whether a fetus has Trisomy 21 during the first trimester of pregnancy based on the differential expression of a combination, or subcombination, of the same.