Guide to Metabolomics Analysis: A Bioinformatics Workflow

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...

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Veröffentlicht in:	Metabolites Jg. 12; H. 4; S. 357
Hauptverfasser:	Chen, Yang, Li, En-Min, Xu, Li-Yan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland MDPI AG 15.04.2022 MDPI
Schlagworte:	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 metabolic pathways summary multi-omics integration algorithms metabolomics analysis tools metabolomics
ISSN:	2218-1989, 2218-1989
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Abstract	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.
AbstractList	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. 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.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.
Author	Chen, Yang Xu, Li-Yan Li, En-Min
AuthorAffiliation	1 The Key Laboratory of Molecular Biology for High Cancer Incidence Coastal Chaoshan Area, Shantou University Medical College, Shantou 515041, China; cy_koasde@163.com 3 Guangdong Provincial Key Laboratory of Infectious Diseases and Molecular Immunopathology, Institute of Oncologic Pathology, Shantou University Medical College, Shantou 515041, China 2 Department of Biochemistry and Molecular Biology, Shantou University Medical College, Shantou 515041, China
AuthorAffiliation_xml	– name: 1 The Key Laboratory of Molecular Biology for High Cancer Incidence Coastal Chaoshan Area, Shantou University Medical College, Shantou 515041, China; cy_koasde@163.com – name: 3 Guangdong Provincial Key Laboratory of Infectious Diseases and Molecular Immunopathology, Institute of Oncologic Pathology, Shantou University Medical College, Shantou 515041, China – name: 2 Department of Biochemistry and Molecular Biology, Shantou University Medical College, Shantou 515041, China
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PublicationDateYYYYMMDD	2022-04-15
PublicationDate_xml	– month: 4 year: 2022 text: 20220415 day: 15
PublicationDecade	2020
PublicationPlace	Switzerland
PublicationPlace_xml	– name: Switzerland – name: Basel
PublicationTitle	Metabolites
PublicationTitleAlternate	Metabolites
PublicationYear	2022
Publisher	MDPI AG MDPI
Publisher_xml	– name: MDPI AG – name: MDPI
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SubjectTerms	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
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Title	Guide to Metabolomics Analysis: A Bioinformatics Workflow
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