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Related Experiment Video

Updated: Mar 1, 2026

Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis

Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis

Published on: November 10, 2023

Bioinformatics can boost metabolomics research.

René Meier¹, Christoph Ruttkies¹, Hendrik Treutler¹

¹Leibniz Institute of Plant Biochemistry, Department of Stress and Developmental Biology, Weinberg 3, 06120 Halle, Germany.

Journal of Biotechnology

|May 31, 2017

Summary

This summary is machine-generated.

Metabolomics, the study of small molecules, is integrating analytical chemistry with cheminformatics and bioinformatics. This evolution enables large-scale data analysis for biological and biochemical research.

Keywords:

Cloud computing Mass spectrometry Metabolite identification Metabolite profiling Metabolomics Workflows

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Related Experiment Videos

Last Updated: Mar 1, 2026

Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis

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A Strategy for Sensitive, Large Scale Quantitative Metabolomics

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Published on: May 27, 2014

Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics

Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics

Published on: November 29, 2024

Area of Science:

Biochemistry
Bioinformatics
Cheminformatics

Background:

Metabolomics is the study of small molecules in biological systems.
It combines analytical chemistry with computational methods.
The field is evolving towards large-scale data analysis.

Purpose of the Study:

To provide background on the historical development of metabolomics.
To highlight current state-of-the-art methodologies in the field.
To outline future requirements for advancing metabolomics research.

Main Methods:

Review of historical analytical chemistry techniques.
Integration of cheminformatics tools.
Application of bioinformatics for data analysis.

Main Results:

The field is transitioning to incorporate advanced computational approaches.
Current methods enable sophisticated analysis of small molecule data.
Future directions focus on scalable data processing and interpretation.

Conclusions:

Metabolomics is rapidly advancing through interdisciplinary integration.
Computational methods are crucial for handling complex biological data.
Future research requires enhanced infrastructure for large-scale metabolomic studies.