Evidence map›Paper›PMID 28970795›Full record

ArticleFrontiers in pharmacology2017

Transcriptome Profiling in Systems Vascular Medicine.

Suowen Xu

Abstract read
In one paragraph

Article in Frontiers in pharmacology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 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

1 author.

Suowen XuDepartment of Medicine, Aab Cardiovascular Research Institute, University of Rochester School of Medicine and Dentistry, RochesterNY, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the post-genomic, big data era, our understanding of vascular diseases has been deepened by multiple state-of-the-art "-omics" approaches, including genomics, epigenomics, transcriptomics, proteomics, lipidomics and metabolomics. Genome-wide transcriptomic profiling, such as gene microarray and RNA-sequencing, emerges as powerful research tools in systems medicine and revolutionizes transcriptomic analysis of the pathological mechanisms and therapeutics of vascular diseases. In this article, I will highlight the workflow of transcriptomic profiling, outline basic bioinformatics analysis, and summarize recent gene profiling studies performed in vascular cells as well as in human and mice diseased samples. Further mining of these public repository datasets will shed new light on our understanding of the cellular basis of vascular diseases and offer novel potential targets for therapeutic intervention.

Indexed as

gene profilinglong non-coding RNAmicroarrayRNA-sequencingtranscriptomevascular medicine

Identifiers

PMID28970795
PMCPMC5609594

What OpenQuestion holds

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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.