Evidence map›Paper›PMID 27649151›Full record

ReviewInternational journal of molecular sciences2016

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

Abdellah Tebani, Carlos Afonso, Stéphane Marret, Soumeya Bekri

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in International journal of molecular sciences, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 99 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
99citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

99 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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39 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Abdellah TebaniDepartment of Metabolic Biochemistry, Rouen University Hospital, 76031 Rouen, France. abdellah.tebani@chu-rouen.fr.
Carlos AfonsoNormandie University, UNIROUEN, INSA Rouen, CNRS, COBRA, 76000 Rouen, France. carlos.afonso@univ-rouen.fr.
Stéphane MarretNormandie University, UNIROUEN, INSERM, CHU Rouen, Laboratoire NeoVasc ERI28, 76000 Rouen, France. stephane.marret@chu-rouen.fr.
Soumeya BekriDepartment of Metabolic Biochemistry, Rouen University Hospital, 76031 Rouen, France. soumeya.bekri@chu-rouen.fr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

EpigenomicsGene Expression ProfilingGenomicsHumansMetabolism, Inborn ErrorsMetabolomicsPrecision MedicineProteomicsSensitivity and SpecificitySystems Biologybioinformaticsbiomarkerschemometricsdata integrationinborn errors of metabolismmachine learningmass spectrometrynext-generation sequencingomicsprecision medicine

Identifiers

PMID27649151
PMCPMC5037827

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.