Computational and statistical analysis of metabolomics data
How do you Analyse metabolomics data?
Metabolomics data analysis usually consists of feature extraction, compound identification, statistical analysis and interpretation. Data analysis is a significant part of the metabolomics workflow, with compound identification being the major bottleneck..
What are the analytical techniques used in metabolomics?
Nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry are the two analytical instruments most frequently applied in metabolomics research. NMR spectroscopy applies the magnetic properties of atomic nuclei in a metabolite..
What are the statistical methods of metabolomics?
Two main statistical approaches are available for metabolite differential level analysis: univariate and multivariate. Combination of both methodologies is common to metabolomic biomarker-based studies but this review shall focus on the advantages and increased power gained from multivariate analysis (MVA).Jun 15, 2023.
What is computational metabolomics?
The computational metabolomics field brings together computer scientists, bioinformaticians, chemists, clinicians, and biologists to maximize the impact of metabolomics across a wide array of scientific and medical disciplines..
Where can I upload metabolomics data?
The Metabolomics Workbench, available at www.metabolomicsworkbench.org, is a public repository for metabolomics metadata and experimental data spanning various species and experimental platforms, metabolite standards, metabolite structures, protocols, tutorials, and training material and other educational resources..
Nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry are the two analytical instruments most frequently applied in metabolomics research. NMR spectroscopy applies the magnetic properties of atomic nuclei in a metabolite.
The computational metabolomics field brings together computer scientists, bioinformaticians, chemists, clinicians, and biologists to maximize the impact of metabolomics across a wide array of scientific and medical disciplines.
Jul 28, 2015By assaying and analyzing thousands of metabolites in biological samples, it provides a whole picture of metabolic status and biochemical events
Jul 28, 2015Metabolomics is the comprehensive study of small molecule metabolites in biological systems. By assaying and analyzing thousands of
Jul 28, 2015The purpose of metabolic databases is to organize the many metabolites in a way that helps researchers easily identify and analyze metabolomics
What are the major metabolomics databases?
Among the databases are the Human Metabolome Database (HMDB), MassBank, METLIN, lipid metabolites and pathways strategy (LIPID MAPS), Madison metabolomics consortium database, and Kyoto Encyclopedia of Genes and Genomes (KEGG)
What is computational methods and data analysis for metabolomics?
Authoritative and cutting-edge, Computational Methods and Data Analysis for Metabolomics to ensure successful results in the further study of this vital field
This book provides a comprehensive guide to scientists, engineers, and students that employ metabolomics in their work, with an emphasis on the understanding and interpretation of the data
What statistical concepts have been applied to high-throughput metabolomics data?
In the remainder of this mini review, two statistical concepts recently applied to high-throughput metabolomics data by our group will be especially emphasized: network modeling based on Gaussian graphical models (GGMs) and higher-order correlation analysis denoted as independent component analysis (ICA)
In computational biology and bioinformatics, analysis of variance – simultaneous component analysis is a method that partitions variation and enables interpretation of these partitions by SCA, a method that is similar to principal components analysis (PCA). Analysis of variance (ANOVA) is a collection of statistical models and their associated estimation procedures used to analyze differences. Statistical coupling analysis (SCA) is a technique used in bioinformatics to measure covariation between pairs of amino acids in a protein multiple sequence alignment (MSA).
Computational and statistical analysis of metabolomics data
Scientific study of chemical processes involving metabolites
Metabolomics is the scientific study of chemical processes involving metabolites, the small molecule substrates, intermediates, and products of cell metabolism. Specifically, metabolomics is the systematic study of the unique chemical fingerprints that specific cellular processes leave behind, the study of their small-molecule metabolite profiles. The metabolome represents the complete set of metabolites in a biological cell, tissue, organ, or organism, which are the end products of cellular processes. Messenger RNA (mRNA), gene expression data, and proteomic analyses reveal the set of gene products being produced in the cell, data that represents one aspect of cellular function. Conversely, metabolic profiling can give an instantaneous snapshot of the physiology of that cell, and thus, metabolomics provides a direct functional readout of the physiological state of an organism. There are indeed quantifiable correlations between the metabolome and the other cellular ensembles, which can be used to predict metabolite abundances in biological samples from, for example mRNA abundances. One of the ultimate challenges of systems biology is to integrate metabolomics with all other -omics information to provide a better understanding of cellular biology.
