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Metabolomics. 2018;14(4):37. doi: 10.1007/s11306-018-1335-y. Epub 2018 Feb 27.

From correlation to causation: analysis of metabolomics data using systems biology approaches.

Author information

1
1Magnetic Resonance Center and Department of Chemistry "Ugo Schiff", University of Florence, Florence, Italy.
2
2Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy.
3
3CIBER de Enfermedades hepáticas y digestivas (CIBERHD, Madrid) and Department of Biochemistry and Molecular Biomedicine, Universitat de Barcelona, Barcelona, Spain.
4
4Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Wageningen, The Netherlands.
5
5LifeGlimmer GmbH, Berlin, Germany.

Abstract

Introduction:

Metabolomics is a well-established tool in systems biology, especially in the top-down approach. Metabolomics experiments often results in discovery studies that provide intriguing biological hypotheses but rarely offer mechanistic explanation of such findings. In this light, the interpretation of metabolomics data can be boosted by deploying systems biology approaches.

Objectives:

This review aims to provide an overview of systems biology approaches that are relevant to metabolomics and to discuss some successful applications of these methods.

Methods:

We review the most recent applications of systems biology tools in the field of metabolomics, such as network inference and analysis, metabolic modelling and pathways analysis.

Results:

We offer an ample overview of systems biology tools that can be applied to address metabolomics problems. The characteristics and application results of these tools are discussed also in a comparative manner.

Conclusions:

Systems biology-enhanced analysis of metabolomics data can provide insights into the molecular mechanisms originating the observed metabolic profiles and enhance the scientific impact of metabolomics studies.

KEYWORDS:

Association network; Correlation network; Enrichment analysis; Network analysis; Pathway

Conflict of interest statement

Compliance with ethical standardsAll authors declare that they have no conflict of interest.This article does not contain any studies with human participants or animals performed by any of the authors.

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