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Understanding Metabolomics in Biomedical Research
Endocrinology and Metabolism ; : 7-16, 2016.
Article in English | WPRIM | ID: wpr-186237
ABSTRACT
The term "omics" refers to any type of specific study that provides collective information on a biological system. Representative omics includes genomics, proteomics, and metabolomics, and new omics is constantly being added, such as lipidomics or glycomics. Each omics technique is crucial to the understanding of various biological systems and complements the information provided by the other approaches. The main strengths of metabolomics are that metabolites are closely related to the phenotypes of living organisms and provide information on biochemical activities by reflecting the substrates and products of cellular metabolism. The transcriptome does not always correlate with the proteome, and the translated proteome might not be functionally active. Therefore, their changes do not always result in phenotypic alterations. Unlike the genome or proteome, the metabolome is often called the molecular phenotype of living organisms and is easily translated into biological conditions and disease states. Here, we review the general strategies of mass spectrometry-based metabolomics. Targeted metabolome or lipidome analysis is discussed, as well as nontargeted approaches, with a brief explanation of the advantages and disadvantages of each platform. Biomedical applications that use mass spectrometry-based metabolomics are briefly introduced.
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Full text: Available Index: WPRIM (Western Pacific) Main subject: Phenotype / Mass Spectrometry / Complement System Proteins / Genome / Proteome / Genomics / Proteomics / Glycomics / Metabolome / Metabolomics Language: English Journal: Endocrinology and Metabolism Year: 2016 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Main subject: Phenotype / Mass Spectrometry / Complement System Proteins / Genome / Proteome / Genomics / Proteomics / Glycomics / Metabolome / Metabolomics Language: English Journal: Endocrinology and Metabolism Year: 2016 Type: Article