Evidence map›Paper›PMID 25798438›Full record

ReviewFrontiers in bioengineering and biotechnology2015

Analytical methods in untargeted metabolomics: state of the art in 2015.

Arnald Alonso, Sara Marsal, Antonio Julià

Abstract readReview
In one paragraph

Review in Frontiers in bioengineering and biotechnology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 282 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
282citing papers in PubMed, 3 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

282 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Salivary metabolites to detect patients with cancer: a systematic review.International journal of clinical oncology · 2020
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222 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

3 authors.

Arnald AlonsoRheumatology Research Group, Vall d'Hebron Research Institute , Barcelona , Spain ; Department of Automatic Control (ESAII), Polytechnic University of Catalonia , Barcelona , Spain.
Sara MarsalRheumatology Research Group, Vall d'Hebron Research Institute , Barcelona , Spain.
Antonio JuliàRheumatology Research Group, Vall d'Hebron Research Institute , Barcelona , Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metabolomics comprises the methods and techniques that are used to measure the small molecule composition of biofluids and tissues, and is actually one of the most rapidly evolving research fields. The determination of the metabolomic profile - the metabolome - has multiple applications in many biological sciences, including the developing of new diagnostic tools in medicine. Recent technological advances in nuclear magnetic resonance and mass spectrometry are significantly improving our capacity to obtain more data from each biological sample. Consequently, there is a need for fast and accurate statistical and bioinformatic tools that can deal with the complexity and volume of the data generated in metabolomic studies. In this review, we provide an update of the most commonly used analytical methods in metabolomics, starting from raw data processing and ending with pathway analysis and biomarker identification. Finally, the integration of metabolomic profiles with molecular data from other high-throughput biotechnologies is also reviewed.

Indexed as

data analysisintegrationmass spectrometrymetabolomicsnuclear magnetic resonancepathway analysisspectral processinguntargeted

Identifiers

PMID25798438
PMCPMC4350445

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.