Abstract: A method of identifying a biopolymer in a sample that includes one or more biopolymers. The biopolymers may be polypeptides, polynucleotides, or polysaccharides. The method makes use of mass spectral datasets. A first dataset includes measured masses of the one or more biopolymers that are in the sample. A second dataset includes measured masses of a collection of fragments of the one or more biopolymers. The method selects a mass from the first dataset and then matches masses from the second dataset with the selected mass. The matched masses represent fragments of the biopolymer with the selected mass. Once the masses in the second dataset have been matched they are compared to determine a monomer sequence for the biopolymer with the selected mass. The method may be repeated with additional masses in the first dataset.

Abstract: Described are techniques for processing data sets produced by analyzing a sample. The input data set is represented as rows of intensities over time for a particular mass to charge (m/z) range. A correlation matrix is produced in which each row of the input data set is correlated with every other row in the input data set. The correlation matrix is clustered or grouped such that those highly correlated m/z ranges are included in the same group. A set of one or more scans is selected for each group representing periods of interest within each group. Using the m/z values included in each cluster, a resultant sample spectra is created for each of the selected scans. The processing techniques may be used to identify parent and related fragment ions in the input data set and as a preprocessor producing resultant sampled spectra used as input to subsequent processing.

Abstract: Methods, systems and computer readable media for identifying peaks in a three-dimensional mass spectrometry/elution time dataset. The dataset is represented as a matrix of intensity values with column and row positions corresponding to specific elution time and m/z value, respectively. Peaks may be detected using a watershed image segmentation technique. Further provided are methods, systems and recordable media for creating a mask matrix to be overlaid on a large three-dimensional dataset represented as an image matrix, to identify a much smaller portion of the three dimensional dataset of interest, and to greatly reduce the amount of subsequent processing required for processing data of interest. The mask matrix has the same dimension as the image matrix and includes areas corresponding to one or more peaks identified by the watershed segmentation technique.

Abstract: A method of identifying a biopolymer in a sample that includes one or more biopolymers. The biopolymers may be polypeptides, polynucleotides, or polysaccharides. The method makes use of mass spectral datasets. A first dataset includes measured masses of the one or more biopolymers that are in the sample. A second dataset includes measured masses of a collection of fragments of the one or more biopolymers. The method selects a mass from the first dataset and then matches masses from the second dataset with the selected mass. The matched masses represent fragments of the biopolymer with the selected mass. Once the masses in the second dataset have been matched they are compared to determine a monomer sequence for the biopolymer with the selected mass. The method may be repeated with additional masses in the first dataset.

Abstract: Described are techniques for processing data sets produced by analyzing a sample. The input data set is represented as rows of intensities over time for a particular mass to charge (m/z) range. A correlation matrix is produced in which each row of the input data set is correlated with every other row in the input data set. The correlation matrix is clustered or grouped such that those highly correlated m/z ranges are included in the same group. A set of one or more scans is selected for each group representing periods of interest within each group. Using the m/z values included in each cluster, a resultant sample spectra is created for each of the selected scans. The processing techniques may be used to identify parent and related fragment ions in the input data set and as a preprocessor producing resultant sampled spectra used as input to subsequent processing.

Abstract: Proteins in a sample are subjected to a computational digest to provide a set of predictive peptides for the protein. The predictive set of peptides are analyzed for their degree of prediction for the protein and rank-ordered to create a set of optimal predictor peptides. The optimal predictor peptides are then used to provide m/z ranges to the control software for the mass spectrometer to use as recommendations for ion selection for second stage analysis.

Abstract: A configuration system for an application having a plurality of application components is described. The configuration system includes a configuration oracle/initiator that repeatedly asserts a desired state to the application components to operate in that desired state. The desired state is a predetermined state. The configuration oracle only asserts the desired state to the application components and does not control the manner in which each of the application components moves to the desired state. The configuration system also includes a configuration engine in each of the application components that causes the corresponding application components to move to the desired state upon receiving the state assertion of the desired state unless the configuration engine determines that the corresponding application component is already in the desired state. A method of configuring an application having a large number of application components is also described.

Abstract: A generic notifications framework (GNF) system integrates information from different protocols in a management station interfaced with a network and permits correlation of the information to make more sophisticated management decisions. The generic notifications framework system has one or more protocol-specific translators in communication with the network, a generic notifications framework in communication with the translators, and one or more consumer components in communication with the framework. The translators receive event data elements corresponding with different management protocols from the network and translate the event data elements into respective canonical data structures.

Abstract: A generic notifications framework (GNF) system integrates information from different protocols in a management station interfaced with a network and permits correlation of the information to make more sophisticated management decisions. The generic notifications framework system has one or more protocol-specific translators in communication with the network, a generic notifications framework in communication with the translators, and one or more consumer components in communication with the framework. The translators receive event data elements corresponding with different management protocols from the network and translate the event data elements into respective canonical data structures.