scholarly journals Statistical Analysis and Modeling of Mass Spectrometry-Based Metabolomics Data

2014 ◽  
pp. 333-353 ◽  
Author(s):  
Bowei Xi ◽  
Haiwei Gu ◽  
Hamid Baniasadi ◽  
Daniel Raftery
Keyword(s):  
Mass Spectrometry ◽  
Statistical Analysis ◽  
Metabolomics Data

Advancements in capturing and mining mass spectrometry data are transforming natural products research

2021 ◽  
Author(s):  
Scott A. Jarmusch ◽  
Justin J. J. van der Hooft ◽  
Pieter C. Dorrestein ◽  
Alan K. Jarmusch
Keyword(s):  
Mass Spectrometry ◽  
Data Mining ◽  
Natural Products ◽  
Data Analysis ◽  
Community Participation ◽  
Mass Spectrometry Data ◽  
Metabolomics Data ◽  
Analysis Tools ◽  
Public Data ◽  
Potential Use

This review covers the current and potential use of mass spectrometry-based metabolomics data mining in natural products. Public data, metadata, databases and data analysis tools are critical. The value and success of data mining rely on community participation.

scholarly journals Unveiling trends in soot nucleation and growth: When secondary ion mass spectrometry meets statistical analysis

Carbon ◽  
2019 ◽  
Vol 144 ◽  
pp. 815-830 ◽  
Author(s):  
Cornelia Irimiea ◽  
Alessandro Faccinetto ◽  
Xavier Mercier ◽  
Ismael-Kenneth Ortega ◽  
Nicolas Nuns ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Statistical Analysis ◽  
Secondary Ion Mass Spectrometry ◽  
Nucleation And Growth ◽  
Ion Mass Spectrometry ◽  
Secondary Ion

scholarly journals Differences in the metabolite profiles of tender leaves of wheat, barley, rye and Triticale based on LC-MS

2020 ◽  
Author(s):  
Piyi Xing ◽  
Zhenqiao Song ◽  
Xingfeng Li
Keyword(s):  
Mass Spectrometry ◽  
Liquid Chromatography ◽  
Principal Component ◽  
Liquid Chromatography Mass Spectrometry ◽  
Metabolomics Data ◽  
Chromatography Mass Spectrometry ◽  
Metabolite Profiles ◽  
Positive Mode ◽  
Sugar Derivatives ◽  
Important Basis

AbstractWheatgrass has emerged as a functional food source in recent years, but the detailed metabolomics basis for its health benefits remains poorly understood. In this study, liquid chromatography-mass spectrometry (LC-MS) analysis were used to study the metabolic profiling of seedlings from wheat, barley, rye and triticale, which revealed 1800 features in positive mode and 4303 features in negative mode. Principal component analysis (PCA) showed clear differences between species, and 164 differentially expressed metabolites (DEMs) were detected, including amino acids, organic acids, lipids, fatty acids, nucleic acids, flavonoids, amines, polyamines, vitamins, sugar derivatives and others. Unique metabolites in each species were identified. This study provides a glimpse into the metabolomics profiles of wheat and its wild relatives, which may form an important basis for nutrition, health and other parameters.Practical ApplicationThis manuscript present liquid chromatography-mass spectrometry (LC-MS) results of young sprouts of common wheat and its relatives. Our results may help to better understand the natural variation due to the genotype before metabolomics data are considered for application to wheatgrass and can provide a basis (assessment) for its potential pharmaceutical and nutritional value.

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