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Metabolomics Data Processing and Data Analysis—Current Best Practices
| Metabolomics Data Processing and Data Analysis—Current Best Practices |
| Autore | Hanhineva Kati |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (276 p.) |
| Soggetto topico | Research & information: general |
| Soggetto non controllato |
metabolic networks
mass spectral libraries metabolite annotation metabolomics data mapping nontarget analysis liquid chromatography mass spectrometry compound identification tandem mass spectral library forensics wastewater gut microbiome meta-omics metagenomics metabolomics metabolic reconstructions genome-scale metabolic modeling constraint-based modeling flux balance host–microbiome metabolism global metabolomics LC-MS spectra processing pathway analysis enrichment analysis mass spectrometry liquid chromatography MS spectral prediction metabolite identification structure-based chemical classification rule-based fragmentation combinatorial fragmentation time series PLS NPLS variable selection bootstrapped-VIP data repository computational metabolomics reanalysis lipidomics data processing triplot multivariate risk modeling environmental factors disease risk chemical classification in silico workflows metabolome mining molecular families networking substructures mass spectrometry imaging metabolomics imaging biostatistics ion selection algorithms liquid chromatography high-resolution mass spectrometry data-independent acquisition all ion fragmentation targeted analysis untargeted analysis R programming full-scan MS/MS processing R-MetaboList 2 liquid chromatography–mass spectrometry (LC/MS) fragmentation (MS/MS) data-dependent acquisition (DDA) simulator in silico untargeted metabolomics liquid chromatography–mass spectrometry (LC-MS) experimental design sample preparation univariate and multivariate statistics metabolic pathway and network analysis LC–MS metabolic profiling computational statistical unsupervised learning supervised learning |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557354403321 |
Hanhineva Kati
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Recent Advances in Volatile Organic Compound Analysis as Diagnostic Biomarkers
| Recent Advances in Volatile Organic Compound Analysis as Diagnostic Biomarkers |
| Autore | Drabińska Natalia |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (224 p.) |
| Soggetto topico |
Research & information: general
Chemistry |
| Soggetto non controllato |
liquid–liquid extraction
volatile compounds urine method optimization GC-MS 1H-NMR iron deficiency anaemia iron supplementation volatile organic compounds (VOCs) intestinal metabolome gut microbiome CDH microbiome VOCs spiroergometry outcome exhaled breath eNose smoking asthma COPD NTD-GC-MS breath lung cancer biomarkers volatile organic compounds urine analysis comprehensive two-dimensional gas chromatography kidney diseases urinary biomarkers hepatocellular carcinoma diagnosis headspace analysis untargeted analysis breath analysis cancer biomarkers volatolomics whole grain rye comprehensive two-dimensional gas chromatography–mass spectrometry dietary fiber e-nose electronic nose breathing rhythm mechanical ventilation anesthesia supplemental oxygen oxygen toxicity lipid peroxidation volatile aldehydes pentanal hexanal classification models dairy cows fecal headspace Mycobacterium avium ssp. paratuberculosis (MAP) paratuberculosis random forest stable air volatile organic compound (VOC) biomarker MCC–IMS ventilator-induced lung injury metabolome feces neonates fermentation protein carbohydrate short chain fatty acid metabolites volatile organic compound acute gastritis antibiotic treatment treatment dynamics: microbiota mid-infrared spectroscopy short-chain fatty acid alpha-keto acid Helicobacter pylori MOX sensors low sensing chamber volume calibration transfer standard samples piecewise direct standardization correlation alignment breath sampling pattern recognition |
| ISBN | 3-0365-5349-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910619463903321 |
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Drabińska Natalia
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| MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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