Borges et al., 2021 - Google Patents
Quantum chemistry calculations for metabolomics: Focus reviewBorges et al., 2021
View HTML- Document ID
- 4497005843687429168
- Author
- Borges R
- Colby S
- Das S
- Edison A
- Fiehn O
- Kind T
- Lee J
- Merrill A
- Merz Jr K
- Metz T
- Nunez J
- Tantillo D
- Wang L
- Wang S
- Renslow R
- Publication year
- Publication venue
- Chemical reviews
External Links
Snippet
A primary goal of metabolomics studies is to fully characterize the small-molecule composition of complex biological and environmental samples. However, despite advances in analytical technologies over the past two decades, the majority of small molecules in …
- 230000001431 metabolomic 0 title abstract description 73
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by the preceding groups
- G01N33/48—Investigating or analysing materials by specific methods not covered by the preceding groups biological material, e.g. blood, urine; Haemocytometers
- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
- G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
- G01N33/6803—General methods of protein analysis not limited to specific proteins or families of proteins
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by the preceding groups
- G01N33/48—Investigating or analysing materials by specific methods not covered by the preceding groups biological material, e.g. blood, urine; Haemocytometers
- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
- G01N33/5005—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
- G06F19/18—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for functional genomics or proteomics, e.g. genotype-phenotype associations, linkage disequilibrium, population genetics, binding site identification, mutagenesis, genotyping or genome annotation, protein-protein interactions or protein-nucleic acid interactions
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
- G06F19/12—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for modelling or simulation in systems biology, e.g. probabilistic or dynamic models, gene-regulatory networks, protein interaction networks or metabolic networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
- G06F19/28—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for programming tools or database systems, e.g. ontologies, heterogeneous data integration, data warehousing or computing architectures
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
- G06F19/16—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for molecular structure, e.g. structure alignment, structural or functional relations, protein folding, domain topologies, drug targeting using structure data, involving two-dimensional or three-dimensional structures
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
- G06F19/24—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for machine learning, data mining or biostatistics, e.g. pattern finding, knowledge discovery, rule extraction, correlation, clustering or classification
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/70—Chemoinformatics, i.e. data processing methods or systems for the retrieval, analysis, visualisation, or storage of physicochemical or structural data of chemical compounds
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Borges et al. | Quantum chemistry calculations for metabolomics: Focus review | |
Zhou et al. | Ion mobility collision cross-section atlas for known and unknown metabolite annotation in untargeted metabolomics | |
Pezzatti et al. | Implementation of liquid chromatography–high resolution mass spectrometry methods for untargeted metabolomic analyses of biological samples: A tutorial | |
Chen et al. | Metabolite discovery through global annotation of untargeted metabolomics data | |
Pino et al. | The Skyline ecosystem: Informatics for quantitative mass spectrometry proteomics | |
Shen et al. | Metabolic reaction network-based recursive metabolite annotation for untargeted metabolomics | |
Cui et al. | Challenges and emergent solutions for LC‐MS/MS based untargeted metabolomics in diseases | |
Colby et al. | ISiCLE: a quantum chemistry pipeline for establishing in silico collision cross section libraries | |
Warth et al. | Exposome-scale investigations guided by global metabolomics, pathway analysis, and cognitive computing | |
Wheelock et al. | Application of’omics technologies to biomarker discovery in inflammatory lung diseases | |
Li et al. | MetDIA: targeted metabolite extraction of multiplexed MS/MS spectra generated by data-independent acquisition | |
Rasche et al. | Identifying the unknowns by aligning fragmentation trees | |
Samaraweera et al. | Evaluation of an artificial neural network retention index model for chemical structure identification in nontargeted metabolomics | |
Hill et al. | Mass spectral metabonomics beyond elemental formula: chemical database querying by matching experimental with computational fragmentation spectra | |
Dumas | Metabolome 2.0: quantitative genetics and network biology of metabolic phenotypes | |
Drotleff et al. | Guidelines for selection of internal standard-based normalization strategies in untargeted lipidomic profiling by LC-HR-MS/MS | |
Kwiecien et al. | High-resolution filtering for improved small molecule identification via GC/MS | |
Wang et al. | Target-decoy-based false discovery rate estimation for large-scale metabolite identification | |
Price et al. | EBP, a program for protein identification using multiple tandem mass spectrometry datasets | |
Neto et al. | Expanding urinary metabolite annotation through integrated mass spectral similarity networking | |
Ji et al. | KPIC2: an effective framework for mass spectrometry-based metabolomics using pure ion chromatograms | |
Meusel et al. | Predicting the presence of uncommon elements in unknown biomolecules from isotope patterns | |
Malmstrom et al. | Automated workflow for large-scale selected reaction monitoring experiments | |
Wedge et al. | FDRAnalysis: a tool for the integrated analysis of tandem mass spectrometry identification results from multiple search engines | |
Stancliffe et al. | An untargeted metabolomics workflow that scales to thousands of samples for population-based studies |