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Computational approaches for systems metabolomics.
Curr. Opin. Biotechnol. 39, 198-206 (2016)
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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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Genome-wide Association; Data Sets; Integration; Phenotypes; Networks; Biology; Traits; Transcriptomics; Metabolites; Inference
ISSN (print) / ISBN 0958-1669
Zeitschrift Current Opinion in Biotechnology
Quellenangaben Band: 39, Seiten: 198-206
Institut(e) Institute of Computational Biology (ICB)