Described herein are methods for screening for a disease state. The method may include obtaining multiple data sets and identifying the disease state based on a combination of the data sets. The data sets may include biomolecule measurements obtained by multiple methods, such as through the use of particles and reference biomolecules.
Disclosed herein are methods and compositions for processing biofluid samples. Some such methods may include obtaining a biofluid sample from a subject having a disease state such as lung cancer. The biofluid sample may be contacted with a nanoparticles to adsorb proteins. The proteins may then be ionized or contacted with a detection reagent. Also disclosed herein are compositions comprising proteins coupled to a nanoparticle upon contact of the nanoparticle with a biofluid sample from a subject having a disease.
G01N 33/574 - ImmunoassayBiospecific binding assayMaterials therefor for cancer
G16H 10/40 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for data related to laboratory analysis, e.g. patient specimen analysis
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
3.
METHODS AND SYSTEMS FOR CLASSIFYING PIXELATED RAW MASS SPECTROMETRY DATA
Disclosed herein are systems and methods for direct classification of biological datasets. The datasets may include raw mass spectrometry data (e.g., mass spectrometry readouts). Some aspects include training a classifier for direct classification of raw mass spectrometry data, and some aspects include applying the classifier.
G16B 40/10 - Signal processing, e.g. from mass spectrometry [MS] or from PCR
G06V 20/69 - Microscopic objects, e.g. biological cells or cellular parts
G06V 10/77 - Processing image or video features in feature spacesArrangements for image or video recognition or understanding using pattern recognition or machine learning using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]Blind source separation
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G16B 20/00 - ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
Provided are methods comprising: combining a biological sample with a double-labeled peptide standard comprising a peptide comprising a first label, and comprising a post-translational modification (PTM) comprising a second label; and identifying or measuring, based on the double-labeled peptide standard, an endogenous protein of the biological sample, wherein the endogenous protein comprises the PTM. Further, provided are methods and devices for enriching and/or purifying glycan-modified macromolecules with higher specificity and sensitivity.
Described herein are methods for identifying a biological state such as pancreatic cancer in a subject. For example, a method may include obtaining protein data, transcriptomic data, genomic data, lipidomic data, or metabolomic data of a subject and identifying a likelihood of the subject having pancreatic cancer. The disclosure includes methods of making and using classifiers.
G01N 33/68 - Chemical analysis of biological material, e.g. blood, urineTesting involving biospecific ligand binding methodsImmunological testing involving proteins, peptides or amino acids
C12Q 1/6886 - Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
G01N 33/92 - Chemical analysis of biological material, e.g. blood, urineTesting involving biospecific ligand binding methodsImmunological testing involving lipids, e.g. cholesterol
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
Described herein are methods such as multi-omics methods for assessing a disease. The multi-omics methods may integrate proteomic, transcriptomic, genomic, lipidomic, or metabolomic data. The method screening diseases or disease states. Also described herein are methods for screening for diseases or disease states from biological samples. also described herein are multi-omics databases and methods of using them.
Described herein are methods for screening or testing for a disease state using a biological sample. The method may include using glycoprotein, glycopeptide or glycan measurements in evaluating a biological state. The measurements may be obtained through the use of nanoparticles that adsorb glycoproteins, glycopeptides, or glycans.
G16H 10/40 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for data related to laboratory analysis, e.g. patient specimen analysis
Described herein are methods such as multi-omic methods for assessing a disease such as cancer. The multi-omic methods may integrate proteomic, transcriptomic, genomic, lipidomic, or metabolomic data. The method screening diseases or disease states. Also described herein are methods for screening for diseases or disease states from biological samples. The methods may include assessing whether a nodule, mass, or cyst is cancerous.
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
Disclosed herein are systems and methods for direct classification of biological datasets. The datasets may include raw mass spectrometry data. Some aspects include training a classifier for direct classification of raw data, and some aspects include applying the classifier.
Described herein are methods for screening for a disease state. The method may include obtaining multiple data sets, and identifying the disease state based on a combination of the data sets. The data sets may include biomolecule measurements obtained by multiple methods, such as through the use of particles and reference biomolecules.
Described herein are methods for screening for a disease state. The method may include obtaining multiple data sets, and identifying the disease state based on a combination of the data sets. The data sets may include biomolecule measurements obtained by multiple methods, such as through the use of particles and reference biomolecules.
Described herein are methods for screening for a disease state. The method may include obtaining multiple data sets, and identifying the disease state based on a combination of the data sets. The data sets may include biomolecule measurements obtained by multiple methods, such as through the use of particles and reference biomolecules.
Disclosed herein are systems and methods for direct classification of biological datasets. The datasets may include raw mass spectrometry data. Some aspects include training a classifier for direct classification of raw data, and some aspects include applying the classifier.
G06V 20/69 - Microscopic objects, e.g. biological cells or cellular parts
G06V 10/77 - Processing image or video features in feature spacesArrangements for image or video recognition or understanding using pattern recognition or machine learning using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]Blind source separation
G06V 10/774 - Generating sets of training patternsBootstrap methods, e.g. bagging or boosting
G16B 15/00 - ICT specially adapted for analysing two-dimensional or three-dimensional molecular structures, e.g. structural or functional relations or structure alignment
G16B 40/10 - Signal processing, e.g. from mass spectrometry [MS] or from PCR
15.
DIRECT CLASSIFICATION OF RAW BIOMOLECULE MEASUREMENT DATA
The present disclosure provides a system comprising: a communication interface that receives data over a communication network, the data comprising arrays of intensity values based on mass-to-charge ratios and elution times, wherein the arrays separately correspond to distinct groups of biological species of one or more biological samples; and a computer in communication with the communication interface, wherein the computer comprises one or more computer processors and computer readable medium comprising machine executable code that, upon execution by the one or more computer processors, implements a method comprising: combining the arrays to generate a multi-dimensional image dataset by at least aligning the arrays based on identified mass spectrometry features, applying a classifier to said multi-dimensional image dataset to generate a label corresponding to a biological state.
G16B 40/10 - Signal processing, e.g. from mass spectrometry [MS] or from PCR
G16H 10/40 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for data related to laboratory analysis, e.g. patient specimen analysis
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
Provided are enrichment methods. The methods may be used to enrich macromolecules. The enrichment may be performed with a multifunctional molecule. The multifunctional molecule may include any combination of a delivery moiety, a reactive group, or an enrichment moiety.
C07D 225/08 - Heterocyclic compounds containing rings of more than seven members having one nitrogen atom as the only ring hetero atom condensed with carbocyclic rings or ring systems condensed with two six-membered rings
C07D 413/06 - Heterocyclic compounds containing two or more hetero rings, at least one ring having nitrogen and oxygen atoms as the only ring hetero atoms containing two hetero rings linked by a carbon chain containing only aliphatic carbon atoms
C07D 413/14 - Heterocyclic compounds containing two or more hetero rings, at least one ring having nitrogen and oxygen atoms as the only ring hetero atoms containing three or more hetero rings
G01N 33/532 - Production of labelled immunochemicals
Disclosed herein are methods and compositions for processing biofluid samples. Some such methods may include obtaining a biofluid sample from a subject having a disease state such as lung cancer. The biofluid sample may be contacted with a nanoparticles to adsorb proteins. The proteins may then be ionized or contacted with a detection reagent. Also disclosed herein are compositions comprising proteins coupled to a nanoparticle upon contact of the nanoparticle with a biofluid sample from a subject having a disease.
G01N 33/574 - ImmunoassayBiospecific binding assayMaterials therefor for cancer
G16B 40/10 - Signal processing, e.g. from mass spectrometry [MS] or from PCR
G16H 10/40 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for data related to laboratory analysis, e.g. patient specimen analysis
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
Described herein are methods such as multi-omic methods for assessing a disease such as cancer. The multi-omic methods may integrate proteomic, transcriptomic, genomic, lipidomic, or metabolomic data. The method screening diseases or disease states. Also described herein are methods for screening for diseases or disease states from biological samples. The methods may include assessing whether a nodule, mass, or cyst is cancerous.
Described herein are methods such as multi-omic methods for assessing a disease such as cancer. The multi-omic methods may integrate proteomic, transcriptomic, genomic, lipidomic, or metabolomic data. The method screening diseases or disease states. Also described herein are methods for screening for diseases or disease states from biological samples. The methods may include assessing whether a nodule, mass, or cyst is cancerous.
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
Described herein are methods such as multi-omic methods for assessing a disease such as cancer. The multi-omic methods may integrate proteomic, transcriptomic, genomic, lipidomic, or metabolomic data. The method screening diseases or disease states. Also described herein are methods for screening for diseases or disease states from biological samples. The methods may include assessing whether a nodule, mass, or cyst is cancerous.
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
Disclosed herein are biomarkers associated with a disease state such as lung cancer, and methods of discovering or using biomarkers. Also disclosed herein are classifiers built on biomarkers and methods of detecting the disease state in samples from subjects. The method may include obtaining a data set that includes protein information from a biofluid sample, and may involve using a classifier to identify the sample as indicative of a healthy state, a disease state, or a comorbidity.
G16B 40/10 - Signal processing, e.g. from mass spectrometry [MS] or from PCR
G16H 10/40 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for data related to laboratory analysis, e.g. patient specimen analysis
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
G01N 33/543 - ImmunoassayBiospecific binding assayMaterials therefor with an insoluble carrier for immobilising immunochemicals
Disclosed herein are biomarkers associated with a disease state such as lung cancer, and methods of discovering or using said biomarkers. Also disclosed herein are classifiers built on said biomarkers and methods of detecting the disease state in samples from subjects.
Disclosed herein are biomarkers associated with a disease state such as lung cancer, and methods of discovering or using said biomarkers. Also disclosed herein are classifiers built on said biomarkers and methods of detecting the disease state in samples from subjects.
01 - Chemical and biological materials for industrial, scientific and agricultural use
05 - Pharmaceutical, veterinary and sanitary products
44 - Medical, veterinary, hygienic and cosmetic services; agriculture, horticulture and forestry services
Goods & Services
Diagnostic preparations and reagents for clinical or medical laboratory use. Diagnostic preparations, agents, and substances for medical purposes; medical diagnostic reagents and assays; diagnostic kits comprised of medical diagnostic reagents and assays for testing bodily fluids for use in disease detection. Medical testing for diagnostic or treatment purposes; medical information services, namely, reporting of clinical testing results; providing medical testing to individuals.
44 - Medical, veterinary, hygienic and cosmetic services; agriculture, horticulture and forestry services
Goods & Services
medical testing for diagnostic or treatment purposes; medical information services, namely, reporting of consumer authorized clinical testing results directly to the patient; providing medical testing of fitness and medical consultations to individuals to help them make health, wellness and nutritional changes in their daily living to improve health
