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    • 1. 发明申请
    • APPARATUS AND METHOD FOR IDENTIFYING PEAKS IN LIQUID CHROMATOGRAPHY/MASS SPECTROMETRY DATA AND FOR FORMING SPECTRA AND CHROMATOGRAMS
    • 用于识别液相色谱/质谱分析数据中的峰和用于形成光谱和色谱的装置和方法
    • WO2005079263A2
    • 2005-09-01
    • PCT/US2005004180
    • 2005-02-11
    • WATERS INVESTMENTS LTDGORENSTEIN MARC VPLUMB ROBERT SSTUMPF CHRIS L
    • GORENSTEIN MARC VPLUMB ROBERT SSTUMPF CHRIS L
    • G01N30/72G01N30/86G06K9/00
    • G01N30/8675G01N30/7233G01N30/8617G01N30/8689G06K9/00523H01J49/022
    • 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. Parameters of the peaks are determined and stored for later processing including quantitation, or simplification of chromatograms or spectra by, for example, identifying peaks associating with ions having retention times falling within a specified retention time window or having mass-to charge ratios falling within a specified mass-to-charge ratio window.
    • 通过创建光谱和色谱数据的二维数据矩阵来分析由LC / MS系统产生的色谱图和质谱。 可以通过将由LC / MS系统的质谱仪部分生成的光谱放置在数据矩阵的连续列中来创建二维矩阵。 以这种方式,数据矩阵的行对应于色谱数据,数据矩阵的列对应于光谱。 指定二维滤波器并将其应用于数据矩阵,以增强系统检测与离子相关的峰值的能力。 二维滤波器根据所需的标准进行指定。 可以指定Rank-1和2级滤波器来提高计算效率。 应用二维滤波器的一种方法是通过将数据矩阵与二维滤波器卷积以产生输出数据矩阵。 在输出数据矩阵中识别与检测到的离子相对应的峰。 峰的参数被确定并存储以用于随后的处理,包括定量或简化色谱或光谱,例如通过鉴定与具有落入规定保留时间窗内的保留时间的离子相关联的峰或者具有落入 指定的质荷比窗口。
    • 7. 发明申请
    • A METHOD OF USING DATA BINNING IN THE ANALYSIS OF CHROMATOGRAHPY/SPECTROMETRY DATA
    • 在色谱分析数据分析中使用数据的方法
    • WO03102543A2
    • 2003-12-11
    • PCT/US0317190
    • 2003-05-30
    • WATERS INVESTMENTS LTDPLUMB ROBERT STEPHENSTUMPF CHRIS LEEGORENSTEIN MARC V
    • PLUMB ROBERT STEPHENSTUMPF CHRIS LEEGORENSTEIN MARC V
    • G01N30/86G01N20060101G01N30/62G01N30/72G01N30/74G06F19/24H01J49/00H01J49/04H01J49/16G01N
    • H01J49/0036G01N30/8675G06F19/24
    • Disclosed herein is a method of analyzing three-dimensional data obtainedfrom 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 (R). 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 multi­variant analysis of this type of data between different samples. However, typically, PCA analysis is performed using only two-dimensional data. Therefore, it is expected that at least one parameter of data obtained from a LC/MS operation is lost, however, the methods disclosed herein preserves all three mathematical dimensions.
    • 本文公开了一种分析从色谱/光谱法过程获得的三维数据的方法,特别是使用二维多变量统计分析的LC / MS方法。 LC部分允许分离样品内的分析物。 从这种方法获得的信息通常取决于保留时间(R)。 当分析物通过系统进入时,它们进入LC / MS系统的MS区域。 在那里它们被离子化,质量检测器然后检测这些电离物质。 从该程序获得的信息通常被报告为对应的m / z值的强度。 因此,LC / MS系统提供至少三条信息。 原理分量分析(PCA)是一种对不同样本之间的这种数据进行多变量分析的可靠方法。 然而,通常,仅使用二维数据来执行PCA分析。 因此,期望从LC / MS操作获得的数据的至少一个参数丢失,然而,本文公开的方法保留所有三个数学维度。