Evidence map›Paper›PMID 26743025›Full record

ArticleScientific reports2016

New insights into functional regulation in MS-based drug profiling.

Ana Sofia Carvalho, Henrik Molina, Rune Matthiesen

Abstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–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

11 citing papers in PubMed.

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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.

Ana Sofia CarvalhoComputational and Experimental Biology Group, National Health Institute Dr. Ricardo Jorge, IP, Av. Padre Cruz, 1649-016, Lisbon, Portugal.
Henrik MolinaProteomics Resource Center, The Rockefeller University, 1230 York Avenue, New York, New York 10065-6399.
Rune MatthiesenComputational and Experimental Biology Group, National Health Institute Dr. Ricardo Jorge, IP, Av. Padre Cruz, 1649-016, Lisbon, Portugal.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We present a novel data analysis strategy which combined with subcellular fractionation and liquid chromatography-mass spectrometry (LC-MS) based proteomics provides a simple and effective workflow for global drug profiling. Five subcellular fractions were obtained by differential centrifugation followed by high resolution LC-MS and complete functional regulation analysis. The methodology combines functional regulation and enrichment analysis into a single visual summary. The workflow enables improved insight into perturbations caused by drugs. We provide a statistical argument to demonstrate that even crude subcellular fractions leads to improved functional characterization. We demonstrate this data analysis strategy on data obtained in a MS-based global drug profiling study. However, this strategy can also be performed on other types of large scale biological data.

Indexed as

Cell FractionationCell Line, TumorCell NucleusDrugs, InvestigationalGene ExpressionGene Expression ProfilingHigh-Throughput Screening AssaysHumansLymphocytesMass SpectrometryMicrosomesMitochondriaMolecular Sequence AnnotationProteomeProteomicsDrugs, InvestigationalProteome

Identifiers

PMID26743025
PMCPMC4705526

What OpenQuestion holds

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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.