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      Computational approaches for systems metabolomics.

      1 , 1 ,   2

      Current opinion in biotechnology

      Elsevier BV

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          Abstract

          Systems genetics is defined as the simultaneous assessment and analysis of multi-omics datasets. In the past few years, metabolomics has been established as a robust tool describing an important functional layer in this approach. The metabolome of a biological system represents an integrated state of genetic and environmental factors and has been referred to as a 'link between genotype and phenotype'. In this review, we summarize recent progresses in statistical analysis methods for metabolomics data in combination with other omics layers. We put a special focus on complex, multivariate statistical approaches as well as pathway-based and network-based analysis methods. Moreover, we outline current challenges and pitfalls of metabolomics-focused multi-omics analyses and discuss future steps for the field.

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          Author and article information

          Journal
          Curr. Opin. Biotechnol.
          Current opinion in biotechnology
          Elsevier BV
          1879-0429
          0958-1669
          Jun 2016
          : 39
          Affiliations
          [1 ] Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany; German Center for Diabetes Research (DZD e.V.), Germany.
          [2 ] Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany; Department of Mathematics, Technische Universität München, Garching, Germany. Electronic address: fabian.theis@helmholtz-muenchen.de.
          Article
          S0958-1669(16)30117-3
          10.1016/j.copbio.2016.04.009
          27135552

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