Abstract: A system and method for mass analysis where a sample (102) is separated in a liquid chromatograph (104), and subsequently analyzed in a mass spectrometer (112).

Abstract: Chromatograms and mass spectra produced by an LC/MS system are analyzed by creating a two-dimensional data matrix of the spectral and chromatographic data. The two-dimensional matrix can be created by placing the spectra generated by the mass spectrometer portion of the LC/MS system in successive columns of the data matrix. In this way, the rows of the data matrix correspond to chromatographic data and the columns of the data matrix correspond to the spectra. A two-dimensional filter is specified and applied to the data matrix to enhance the ability of the system to detect peaks associated with ions. The two-dimensional filter is specified according to desired criteria. Rank-1 and rank-2 filters can be specified to improve computational efficiency. One method of applying the two-dimensional filter is through convolution of the data matrix with the two-dimensional filter to produce an output data matrix. Peaks corresponding to detected ions are identified in the output data matrix.

Abstract: Disclosed herein is a method of analyzing three-dimensional data obtained from a chromatography/spectrometry process, in particular an LC/MS process using a two-dimensional multi-variant statistical analysis. The LC portion permits separation of analytes within a sample. The information obtained from such a procedure typically depends on retention time (Rt). As the analytes progress through the system, they enter the MS region of the LC/MS system. There they are ionized and a mass detector then detects these ionized species. The information procured from this procedure is generally reported as intensity for a corresponding m/z value. Therefore, an LC/MS system provides at least three pieces of information. Principle component analysis (PCA) is a robust method of multi-variant analysis of this type of data between different samples. However, typically, PCA analysis is performed using only two-dimensional data.

Abstract: A method of programmatically reducing a set of collected LC-MS or LC-MS/MS data such that true chromatographic and MS peaks are identified for use in Metabonomics is disclosed. The identified peaks are used to create a list of LC/MS, GC/MS, DIOS-MS or MALDI-MS signals and responses for a batch of samples which appear in a Master Entity List. The samples in the Master Entity List are then subjected to isotope de-clustering and adduct removal prior to chemometrics being applied to automatically identify biomarkers. An LC-MS/MS or LC/MS, GC/MS, DIOS-MS or MALDI-MS acquisition list is generated for the signals identified as responsible for the PLS-DA or PCA separation. The LC or GC retention time, exact mass and MS/MS spectrum may be compared to databases of known compounds and identified compounds associated with biological parameters may be stored in a new compound database.

Abstract: A system and method for analyzing data from a gel permeation chromatography (GPC) or size exclusion chromatography (SEC) system fro determining a polymeric sample's radius of gyration. Data from two or more detectors is used with a least-squares minimization fit. A novel method includes the simultaneous determination of a sample's radius of gyration using data from a light scattering detector that collects data from at least two incident angles. Detectors within the inventive method include a multi-angle light scattering (LS) detector, viscometer (V) and a refractive index (RI) detector.

Abstract: Disclosed herein is a method of analyzing three-dimensional data obtained from a chromatography/spectrometry process, in particular an LC/MS process using a two-dimensional multi-variant statistical analysis. The LC portion permits separation of analytes within a sample. The information obtained from such a procedure typically depends on retention time (Rt). As the analytes progress through the system, they enter the MS region of the LC/MS system. There they are ionized and a mass detector then detects these ionized species. The information procured from this procedure is generally reported as intensity for a corresponding m/z value. Therefore, an LC/MS system provides at least three pieces of information. Principle component analysis (PCA) is a robust method of multi-variant analysis of this type of data between different samples. However, typically, PCA analysis is performed using only two-dimensional data.