Computational approaches for systems metabolomics
Krumsiek J, Bartel J, Theis FJ (2016)
Publication Type: Journal article, Review article
Publication year: 2016
Journal
Book Volume: 39
Pages Range: 198-206
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.
Involved external institutions
Germany (DE)How to cite
APA:
Krumsiek, J., Bartel, J., & Theis, F.J. (2016). Computational approaches for systems metabolomics. Current Opinion in Biotechnology, 39, 198-206. https://doi.org/10.1016/j.copbio.2016.04.009
MLA:
Krumsiek, Jan, Joerg Bartel, and Fabian J. Theis. "Computational approaches for systems metabolomics." Current Opinion in Biotechnology 39 (2016): 198-206.
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