1015results about "Molecular entity identification" patented technology

The invention relates, in part, to the improved analysis of carbohydrates. In particular, the invention relates to the analysis of carbohydrates, such as N-glycans and O-glycans found on proteins and saccharides attached to lipids. Improved methods, therefore, for the study of glycosylation patterns on cells, tissue and body fluids are also provided. Information from the analysis of glycans, such as the glycosylation patterns on cells, tissues and in body fluids, can be used in diagnostic and treatment methods as well as for facilitating the study of the effects of glycosylation / altered glycosylation. Such methods are also provided. Methods are further provided to assess production processes, to assess the purity of samples containing glycoconjugates, and to select glycoconjugates with the desired glycosylation.

The present invention is directed generally toward the field of spectral analysis and, more particularly, toward an improved method of identifying unknown components of a mixture from a set of spectra collected from the mixture using a spectral library including potential candidates. For example, the present method is directed to identifying components of a mixture by the steps which comprise obtaining a set of spectral data for the mixture that defines a mixture data space; ranking a plurality of library spectra of known elements according to their angle of projection into the mixture data space; calculating a corrected correlation coefficient for each combination of the top y ranked library spectra; and selecting the combination having the highest corrected correlation coefficient, wherein the known elements of the selected combination are identified as the components of the mixture.

A method for matching precursor ions to product ions generated in a chromatography—mass spectrometry experiment comprises: choosing a time window defining a region of interest for precursor ion data and product ion data generated by the experiment; constructing a plurality of extracted ion chromatograms (XICs) for the precursor ion data and the product ion data within the region of interest; automatically detecting and characterizing chromatogram peaks within each XIC and automatically generating synthetic analytical fit peaks thereof; discarding a subset of the synthetic analytical peaks which do not satisfy noise reduction rules; performing a respective cross-correlation score calculation between each pair of synthetic analytical fit peaks; and recognizing matches between precursor ions and product ions based on the cross correlation scores.

There is provided a method of automatically identifying and characterizing spectral peaks of a spectrum generated by an analytical apparatus and reporting information relating to the spectral peaks to a user, comprising the steps of: receiving the spectrum generated by the analytical apparatus; automatically subtracting a baseline from the spectrum so as to generate a baseline-corrected spectrum; automatically detecting and characterizing the spectral peaks in the baseline-corrected spectrum; and reporting at least one item of information relating to each detected and characterized spectral peak to a user. In embodiments, baseline model curve parameters or peak model curve parameters are neither input by nor exposed to the user prior to the reporting step.

Methods and apparatus for LC / IMS / MS analysis involve obtaining noisy raw data from a sample, convolving the data with an artifact-reducing filter, and locating, in retention-time, ion mobility, and mass-to-charge-ratio dimensions, one or more ion peaks of the convolved data.

Systems and methods are used to store an electronic record of all product ion spectra of all detectable compounds of a sample. A plurality of product ion scans are performed on a tandem mass spectrometer one or more times in a single sample analysis across a mass range using a plurality of mass selection windows. All sample product ion spectra of all detectable compounds for each mass selection window are produced. All sample product ion spectra for each mass selection window are received from the tandem mass spectrometer using a processor. All sample product ion spectra for each mass selection window are stored as an electronic record of all detectable compounds of the sample using the processor. The electronic record is used to characterize compounds known at the time the electronic record is stored or to characterize compounds that became known after the electronic record was stored.

A method of predicting the composition of hydrocarbon products of a complex carbonaceous material when exposed to specific time and temperature conditions is disclosed. In one embodiment, the material is characterized to obtain elemental, chemical and structural parameters. A representative chemical structure of the material is constructed based on the characterization information. The representative chemical structure is then stochastically expanded to a molecular ensemble chemical structural model that includes heteroatoms. The chemical structural model is coupled to a compositional yield model and the composition of the material products is determined using kinetic modeling. Methods are provided of constructing a chemical structural model of complex carbonaceous material, of coupling a molecular ensemble of chemical structures to a thermal chemical mechanism, of updating an ensemble of chemical structures during the kinetic modeling to reflect chemical reaction products and of eliminating molecules from the system.

An improved system and method of analyzing sample data that increases the reliability of peak (compound) detection and identification in the presence of chemical and / or random noise. The sample analysis system includes a compound-separating unit for separating constituent compounds in a sample mixture, a compound-analyzing unit for identifying and quantitating at least one of the separated compounds, and a computer for acquiring data from the compound-separating and compound-analyzing units, for generating a multi-dimensional data set incorporating the acquired data, for executing an algorithm for reducing noise in the data set and for detecting peaks (compounds) in the noise-reduced data set, and for identifying / quantitating the detected compounds.

A system and method for ample analysis including acquiring a tissue sample, preparing the tissue sample for mass spectrometry imaging, conducting a mass spectrometry procedure on the tissue sample to produce an image, analyzing the image to determine the presence or absence of a biomarker; and generating a report indicating a presence or absence of cancer.

Described are computer-based methods and apparatuses, including computer program products, for monitoring, detecting, and quantifying chemical compounds in a sample. A sample measurement comprising a digitized spectroscopic profile is received. A multivariate multistage background model comprising a first model that models a first time effect, a second model that models a second time effect that is different than the first time effect, or both is calculated. A background corrected sample measurement based on the sample measurement and the multivariate multistage background model is generated. A multivariate multistage library search, fault detection, and quantification algorithm is executed to identify one or more primary chemicals in the background corrected sample measurement. The search, detection, and quantification algorithm includes identifying one or more candidate chemicals in the background corrected sample measurement based on a multivariate statistical process control and identifying and quantifying a first primary chemical based on a focused chemical evaluation of the one or more candidate chemicals.

This invention pertains generally to the field of multivariate statistics, and in particular to new methods for the analysis (e.g., chemometrics) of chemical, biochemical, and biological data, including, for example, spectral data, including but not limited to nuclear magnetic resonance (NMR) spectral data. These methods are useful, for example, in metabonomics, proteomics, transcriptomics, genomics, etc., and form a part of other methods, for example, methods for the identification of chemical species, methods for the identification of biomarkers that are useful in methods of classification, diagnosis, prognosis, etc.

A method for analyzing data from a mass spectrometer comprising obtaining calibrated continuum spectral data by processing raw spectral data; obtaining library spectral data which has been processed to form calibrated library data; and performing a least squares fit, preferably using matrix operations (equation 1), between the calibrated continuum spectral data and the calibrated library data to determine concentrations of components in a sample which generated the raw spectral data. A mass spectrometer system (FIG. 1) that operates in accordance with the method, a data library of transformed mass spectra, and a method for producing the data library.

The present disclosure provides methods and systems for determining and / or characterizing one or more haplotypes and / or phasing of haplotypes in a nucleic acid sample. In particular, the disclosure provides methods for determining a haplotype and / or phasing of haplotypes in a nucleic acid sample by incorporating synthetic polymorphisms into fragments of a nucleic acid sample and utilizing the synthetic polymorphisms in determining one or more haplotypes and / or phasing of haplotypes.

Methods using mass spectral data analysis and a classification algorithm provide an ability to determine whether a solid epithelial tumor cancer patient is likely to benefit from a therapeutic agent or a combination of therapeutic agents targeting agonists of the receptors, receptors or proteins involved in MAPK (mitogen-activated protein kinase) pathways or the PKC (protein kinase C) pathway upstream from or at Akt or ERK / JNK / p38 or PKC, such as therapeutic agents targeting EGFR and / or HER2. The methods also provide the ability to determine whether the cancer patient is likely to benefit from the combination of a therapeutic agent targeting EFGR and a therapeutic agent targeting COX2; or whether the cancer patient is likely to benefit from the treatment with an NF-κB inhibitor.

Methods for determining the chemical structures, substructures and / or ionic structural arrangements of unknown or partially structurally characterized compounds from mass spectrometric data are disclosed. The methods of the invention are directed to elucidating the molecular structures of compounds by identifying the structures of ions generated from those compounds through the use of tandem mass spectrometry and subsequently conducting a library search of structurally characterized tandem product spectra from known ions for specific matches. The collective structural information and / or alternative structural candidates are then constructed from the determined ion structures and other structural characteristics using a structure generator and / or a structure assembly and / or a structure reduction system. The structure or substructure determination process can be continuously improved by adding additional data, e.g., information obtained from molecules previously structurally characterized using this method.

There is provided a method of automatically identifying and characterizing spectral peaks of a spectrum generated by an analytical apparatus comprising the steps of: receiving the spectrum generated by the analytical apparatus; automatically subtracting a baseline from the spectrum so as to generate a baseline-corrected spectrum; automatically detecting and characterizing the spectral peaks in the baseline-corrected spectrum; reporting the detected and characterized spectral peaks to a user; receiving a list of adjustments to be made to the detecting and characterizing step from the user; and adjusting exit values used in the detecting and characterizing step, based on the list of adjustments.

The invention relates to a crystal geometrically necessary dislocation automatic analysis method based on synchrotron radiation. The method comprises the following steps: step one, acquiring a binary map, diffraction spot calibration information and crystal orientation information from an original map through the map processing; step two, establishing a dislocation dictionary through the crystallographic theory, establishing equipment model and simulating an elongation direction in combination with the diffraction spot calibration information and the crystal orientation information so as to obtain a candidate elongation direction; step three, using the binary map, the diffraction spot calibration information and the crystal orientation information to compute a diffraction spot elongation or splitting direction and elongation diffraction spot vertex through the graphic computation method of a diffraction map, the position computation method of the diffraction spot position and a rotation matrix method of the crystal orientation; step four, computing the diffraction spot elongation or splitting angle through the elongation diffraction spot vertex and the splitting diffraction spot calibration information; step five, identifying and matching the diffraction spot elongation or splitting according to the candidate elongation direction produced through simulation, computed elongation or splitting direction and elongation or splitting angle.

A method for integrating chemometric model development and chemometric model application to a process system, the method comprising: (1) receiving spectral data from a process system, the received spectral data corresponding to material being monitored by the process system; (2) receiving user input through at least one graphic user interface; (3) developing at least one chemometric model at least partially in response to the received user input; and (4) applying at least one chemometric model to the received spectral data to thereby predict a property of the material being monitored; and wherein the developing step and the applying step are performed by an integrated software program. Systems and software related to this method are also disclosed herein.

A system is provided for analyzing metabolomics data received from an analytical device across a group of samples. The system automatically receives a data matrix corresponding to each of the samples, wherein the data matrix includes rows corresponding to each of the samples and columns corresponding to a group of ions present in the respective samples. A processor is provided for determining a characteristic value corresponding to at least one of a group of components present in the samples, wherein the components are made up of at least a portion of the group of ions, using at least one of a correlation function and a factorization function. A user interface is in communication with the processor for displaying a visual indication of the characteristic value such that a user may receive a visual indication of the types of components present in the samples.

There is provided a method of automatically identifying and characterizing spectral peaks of a spectrum generated by an analytical apparatus comprising the steps of: receiving the spectrum generated by the analytical apparatus; automatically subtracting a baseline from the spectrum so as to generate a baseline-corrected spectrum; automatically detecting and characterizing the spectral peaks in the baseline-corrected spectrum; reporting the detected and characterized spectral peaks to a user; receiving a list of adjustments to be made to the detecting and characterizing step from the user; and adjusting exit values used in the detecting and characterizing step, based on the list of adjustments.

An olfaction processor (OLP) (100) that generates RAW data (35) including content data (139d) relating to chemical substances is provided. The OLP (100) includes a generator (130) that generates the RAW data (35). The chemical substances include at least one of compounds, molecules, and elements. The generator (130) includes a conversion unit (131) that converts intensity variations, which show detected chemical substances included in data from at least one sensor that detects an amount that changes due to presence of at least one of the chemical substances, to the content data (139d) by mapping onto a frequency space where a plurality of frequencies have been respectively assigned to a plurality of specified chemical substances.

A method for non-targeted complex sample analysis which involves the following steps. A first step involves providing a data base containing identifying data of known molecules. A second step involves introducing a complex sample containing multiple unidentified molecules into a Fourier Transform Ion Cyclotron Mass Spectrometer to obtain data regarding the molecules in the complex sample. A third step involves comparing the collected data regarding the molecules in the complex sample with the identifying data of known molecules in order to arrive at an identification through comparison of molecules in the sample.

The invention provides methods and apparatus for characterizing complex polymeric mixture of interest. Candidate solutions are eliminated from a solution space using one or more experimental measurements of a polymeric mixture of interest. The elimination step can be repeated one or more times using different experimental measurements produced by various chemical and physical protocols, so that the remaining candidate solutions converge to describe the actual polymeric mixture under investigation. Once the composition of the complex polymeric mixture has been characterized, the information thus generated can be used to facilitate, for example, the manufacture of a bio-equivalent of the complex polymeric mixture.

A method of mass spectrometry. The method starts with gaining a total ion chromatogram by a mass spectrometer. An accumulation mass spectrum indicating vicinities of a desired peak top of the total ion chromatogram is displayed. The operator selects a desired mass peak from the displayed accumulation mass spectrum. Another mass chromatogram that is coincident in elution start time, maximum elution time, and elution end time with the mass chromatogram of the selected mass peak are extracted and selected out as a mass peak. Thus, a mass spectrum of a single component is reconstructed.

The invention discloses a laser-induced breakdown spectroscopy (LIBS)-based tea classification and identification method, and belongs to the field of spectral analysis. The method comprises the following steps: performing preliminary analysis on elementary composition of a tea sample by using an LIBS detection device and selecting the characteristic spectral line of an element with larger content difference as an analysis index; then collecting a plurality of groups of spectrums for each standard tea sample and dividing the spectrum data of each standard tea sample into two parts, wherein one part is used as a training sample to establish a discriminant analysis model, and the other part is used as a test sample for estimating the accuracy of the discriminant model; performing discriminant analysis on to-be-tested tea sample, then adjusting an established classification model, and comparing with the LIBS spectrum data model of each element in an established database to determine the type of to-be-identified tea. The method has the advantages of high discrimination accuracy and simple process, and can provide a reference method for detection of the tea and the type recognition.

The present invention generally provides systems and methods for the detection, identification, or characterization of differences between properties or behavior of corresponding species in two or more mixtures comprised of molecules, including biomolecules and / or molecules able to interact with biomolecules, using techniques such as partitioning. The experimental conditions established as distinguishing between the mixtures of the molecules using the systems and methods of the invention can also be used, in some cases, for further fractionation and / or characterization of the biomolecules and / or other molecules, using techniques such as single-step or multiple-step extraction, and / or by liquid-liquid partition chromatography. The methods could also be used for discovering and identifying markers associated with specific diagnostics, and can be used for screening for such markers once discovered and identified during diagnostics screening.