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Open AccessReview

Omics-Based Strategies in Precision Medicine: Toward a Paradigm Shift in Inborn Errors of Metabolism Investigations

1
Department of Metabolic Biochemistry, Rouen University Hospital, 76031 Rouen, France
2
Normandie University, UNIROUEN, INSERM, CHU Rouen, Laboratoire NeoVasc ERI28, 76000 Rouen, France
3
Normandie University, UNIROUEN, INSA Rouen, CNRS, COBRA, 76000 Rouen, France
4
Department of Neonatal Pediatrics, Intensive Care and Neuropediatrics, Rouen University Hospital, 76031 Rouen, France
*
Author to whom correspondence should be addressed.
Academic Editor: William Chi-shing Cho
Int. J. Mol. Sci. 2016, 17(9), 1555; https://doi.org/10.3390/ijms17091555
Received: 27 July 2016 / Revised: 6 September 2016 / Accepted: 7 September 2016 / Published: 14 September 2016
(This article belongs to the Special Issue Precision Medicine—From Bench to Bedside)
The rise of technologies that simultaneously measure thousands of data points represents the heart of systems biology. These technologies have had a huge impact on the discovery of next-generation diagnostics, biomarkers, and drugs in the precision medicine era. Systems biology aims to achieve systemic exploration of complex interactions in biological systems. Driven by high-throughput omics technologies and the computational surge, it enables multi-scale and insightful overviews of cells, organisms, and populations. Precision medicine capitalizes on these conceptual and technological advancements and stands on two main pillars: data generation and data modeling. High-throughput omics technologies allow the retrieval of comprehensive and holistic biological information, whereas computational capabilities enable high-dimensional data modeling and, therefore, accessible and user-friendly visualization. Furthermore, bioinformatics has enabled comprehensive multi-omics and clinical data integration for insightful interpretation. Despite their promise, the translation of these technologies into clinically actionable tools has been slow. In this review, we present state-of-the-art multi-omics data analysis strategies in a clinical context. The challenges of omics-based biomarker translation are discussed. Perspectives regarding the use of multi-omics approaches for inborn errors of metabolism (IEM) are presented by introducing a new paradigm shift in addressing IEM investigations in the post-genomic era. View Full-Text
Keywords: omics; next-generation sequencing; mass spectrometry; machine learning; chemometrics; data integration; bioinformatics; biomarkers; inborn errors of metabolism; precision medicine omics; next-generation sequencing; mass spectrometry; machine learning; chemometrics; data integration; bioinformatics; biomarkers; inborn errors of metabolism; precision medicine
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MDPI and ACS Style

Tebani, A.; Afonso, C.; Marret, S.; Bekri, S. Omics-Based Strategies in Precision Medicine: Toward a Paradigm Shift in Inborn Errors of Metabolism Investigations. Int. J. Mol. Sci. 2016, 17, 1555. https://doi.org/10.3390/ijms17091555

AMA Style

Tebani A, Afonso C, Marret S, Bekri S. Omics-Based Strategies in Precision Medicine: Toward a Paradigm Shift in Inborn Errors of Metabolism Investigations. International Journal of Molecular Sciences. 2016; 17(9):1555. https://doi.org/10.3390/ijms17091555

Chicago/Turabian Style

Tebani, Abdellah; Afonso, Carlos; Marret, Stéphane; Bekri, Soumeya. 2016. "Omics-Based Strategies in Precision Medicine: Toward a Paradigm Shift in Inborn Errors of Metabolism Investigations" Int. J. Mol. Sci. 17, no. 9: 1555. https://doi.org/10.3390/ijms17091555

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Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

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