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Guide to Metabolomics Analysis: A Bioinformatics Workflow
by
Chen, Yang
, Xu, Li-Yan
, Li, En-Min
in
Alzheimer's disease
/ Amino acids
/ Bioinformatics
/ Biomarkers
/ Cancer
/ Chromatography
/ Data processing
/ Diabetes
/ Fatty acids
/ Identification
/ Integration
/ Lipids
/ Mass spectrometry
/ Metabolic pathways
/ metabolic pathways summary
/ Metabolism
/ Metabolites
/ Metabolomics
/ metabolomics analysis tools
/ multi-omics integration algorithms
/ NMR
/ Nuclear magnetic resonance
/ Phenotypes
/ Polyamines
/ Proteomics
/ Researchers
/ Review
/ Scientific imaging
/ Software
/ Transcriptomics
2022
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Guide to Metabolomics Analysis: A Bioinformatics Workflow
by
Chen, Yang
, Xu, Li-Yan
, Li, En-Min
in
Alzheimer's disease
/ Amino acids
/ Bioinformatics
/ Biomarkers
/ Cancer
/ Chromatography
/ Data processing
/ Diabetes
/ Fatty acids
/ Identification
/ Integration
/ Lipids
/ Mass spectrometry
/ Metabolic pathways
/ metabolic pathways summary
/ Metabolism
/ Metabolites
/ Metabolomics
/ metabolomics analysis tools
/ multi-omics integration algorithms
/ NMR
/ Nuclear magnetic resonance
/ Phenotypes
/ Polyamines
/ Proteomics
/ Researchers
/ Review
/ Scientific imaging
/ Software
/ Transcriptomics
2022
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Do you wish to request the book?
Guide to Metabolomics Analysis: A Bioinformatics Workflow
by
Chen, Yang
, Xu, Li-Yan
, Li, En-Min
in
Alzheimer's disease
/ Amino acids
/ Bioinformatics
/ Biomarkers
/ Cancer
/ Chromatography
/ Data processing
/ Diabetes
/ Fatty acids
/ Identification
/ Integration
/ Lipids
/ Mass spectrometry
/ Metabolic pathways
/ metabolic pathways summary
/ Metabolism
/ Metabolites
/ Metabolomics
/ metabolomics analysis tools
/ multi-omics integration algorithms
/ NMR
/ Nuclear magnetic resonance
/ Phenotypes
/ Polyamines
/ Proteomics
/ Researchers
/ Review
/ Scientific imaging
/ Software
/ Transcriptomics
2022
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Journal Article
Guide to Metabolomics Analysis: A Bioinformatics Workflow
2022
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Overview
Metabolomics is an emerging field that quantifies numerous metabolites systematically. The key purpose of metabolomics is to identify the metabolites corresponding to each biological phenotype, and then provide an analysis of the mechanisms involved. Although metabolomics is important to understand the involved biological phenomena, the approach’s ability to obtain an exhaustive description of the processes is limited. Thus, an analysis-integrated metabolomics, transcriptomics, proteomics, and other omics approach is recommended. Such integration of different omics data requires specialized statistical and bioinformatics software. This review focuses on the steps involved in metabolomics research and summarizes several main tools for metabolomics analyses. We also outline the most abnormal metabolic pathways in several cancers and diseases, and discuss the importance of multi-omics integration algorithms. Overall, our goal is to summarize the current metabolomics analysis workflow and its main analysis software to provide useful insights for researchers to establish a preferable pipeline of metabolomics or multi-omics analysis.
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