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Krumsiek J, Bartel J, Theis FJ. Computational approaches for systems metabolomics. Curr Opin Biotechnol. 2016;39:198-206doi: 10.1016/j.copbio.2016.04.009.
Krumsiek, J., Bartel, J., & Theis, F. J. (2016). Computational approaches for systems metabolomics. Current opinion in biotechnology, 39198-206. https://doi.org/10.1016/j.copbio.2016.04.009
Krumsiek, Jan, et al. "Computational approaches for systems metabolomics." Current opinion in biotechnology vol. 39 (2016): 198-206. doi: https://doi.org/10.1016/j.copbio.2016.04.009
Krumsiek J, Bartel J, Theis FJ. Computational approaches for systems metabolomics. Curr Opin Biotechnol. 2016 Jun;39:198-206. doi: 10.1016/j.copbio.2016.04.009. Epub 2016 Apr 30. PMID: 27135552.
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Curr Opin Biotechnol. 2016 Jun;39:198-206. doi: 10.1016/j.copbio.2016.04.009. Epub 2016 Apr 30.

Computational approaches for systems metabolomics.

Current opinion in biotechnology

Jan Krumsiek, Jörg Bartel, Fabian J Theis

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: [email protected].

PMID: 27135552 DOI: 10.1016/j.copbio.2016.04.009

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.

Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

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