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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 online resource (276 p.) |
| Soggetto topico | Research & information: general |
| Soggetto non controllato |
all ion fragmentation
biostatistics bootstrapped-VIP chemical classification combinatorial fragmentation compound identification computational metabolomics computational statistical constraint-based modeling data processing data repository data-dependent acquisition (DDA) data-independent acquisition disease risk enrichment analysis environmental factors experimental design flux balance forensics fragmentation (MS/MS) full-scan MS/MS processing genome-scale metabolic modeling global metabolomics gut microbiome host-microbiome in silico in silico workflows ion selection algorithms LC-MS lipidomics liquid chromatography liquid chromatography high-resolution mass spectrometry liquid chromatography mass spectrometry liquid chromatography-mass spectrometry (LC-MS) liquid chromatography-mass spectrometry (LC/MS) mass spectral libraries mass spectrometry mass spectrometry imaging meta-omics metabolic networks metabolic pathway and network analysis metabolic profiling metabolic reconstructions metabolism metabolite annotation metabolite identification metabolome mining metabolomics metabolomics data mapping metabolomics imaging metagenomics molecular families MS spectral prediction multivariate risk modeling networking nontarget analysis NPLS pathway analysis PLS R programming R-MetaboList 2 reanalysis rule-based fragmentation sample preparation simulator spectra processing structure-based chemical classification substructures supervised learning tandem mass spectral library targeted analysis time series triplot univariate and multivariate statistics unsupervised learning untargeted analysis untargeted metabolomics variable selection wastewater |
| 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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Systems Analytics and Integration of Big Omics Data
| Systems Analytics and Integration of Big Omics Data |
| Autore | Hardiman Gary |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 online resource (202 p.) |
| Soggetto topico | Medicine |
| Soggetto non controllato |
algorithm development for network integration
Alzheimer's disease amyloid-beta annotation artificial intelligence biocuration bioinformatics pipelines candidate genes causal inference cell lines challenges chromatin modification class imbalance clinical data cognitive impairment curse of dimensionality data integration database deep phenotype dementia direct effect disease variants distance correlation drug sensitivity enrichment analysis epidemiological data epigenetics feature selection Gene Ontology gene-environment interactions genomics genotype heterogeneous data indirect effect integrative analytics joint modeling KEGG pathways logic forest machine learning microtubule-associated protein tau miRNA-gene expression networks missing data multi-omics multiomics integration multivariate analysis multivariate causal mediation n/a network topology analysis neurodegeneration non-omics data omics data pharmacogenomics phenomics phenotype plot visualization precision medicine informatics proteomic analysis regulatory genomics RNA expression scalability sequencing support vector machine systemic lupus erythematosus tissue classification tissue-specific expressed genes transcriptome |
| ISBN | 3-03928-745-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910404089603321 |
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Hardiman Gary
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| MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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