Evidence map›Paper›PMID 30320387›Full record

ArticleMolecular medicine reports2018

Mining the potential therapeutic targets for coronary artery disease by bioinformatics analysis.

Wendong Wang, Zhiwei Xu, Xiaobo Zhu, Xiaotong Chang

Open access · hybridAbstract read
In one paragraph

Article in Molecular medicine reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 52% of its field
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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Article
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 at 1 institution in 1 country.

Wendong WangDepartment of Biochemistry, College of Laboratory Medicine, Hebei North University, Zhangjiakou, Hebei 075000, P.R. China.
Zhiwei XuDepartment of Biochemistry, College of Laboratory Medicine, Hebei North University, Zhangjiakou, Hebei 075000, P.R. China.
Xiaobo ZhuDepartment of Biochemistry, College of Laboratory Medicine, Hebei North University, Zhangjiakou, Hebei 075000, P.R. China.
Xiaotong ChangDepartment of Biochemistry, College of Laboratory Medicine, Hebei North University, Zhangjiakou, Hebei 075000, P.R. China.
Hebei North University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The present study aimed to mine therapeutic molecular targets that play an important part in the progression of coronary artery disease (CAD). The gene expression profile GSE28829 dataset and the microRNA (miRNA) expression profile GSE59421 dataset were downloaded from the Gene Expression Omnibus (GEO) database. The GEO2R online analytical tool was used to identify differentially expressed genes (DEGs) and miRNAs (DEMs). The target genes of DEMs were identified using the miRWalk2.0 web‑based tool and 2 miRNA‑gene regulatory networks were constructed using Cytoscape software. Subsequently, enriched Gene Ontology (GO) terms of miRNA‑target DEGs were obtained using the Database for Visualization, Annotation and Integrated Analysis, and locations of these genes in the chromosomes were determined by Map Viewer. In the present study, 350 DEGs and 66 DEMs were screened. A total of 3,588 target genes were identified from the DEMs, and 57 of these target genes and established DEGs were identified to overlap. GO terms associated with 5 processes, and 4 types of composition were identified to be enriched in the miRNA‑target DEGs. Furthermore, 26 miRNA‑gene regulatory pairs were obtained between the 57 target genes and DEMs. The 26 miRNA‑target DEGs were unevenly distributed, and no genes were located on the sex chromosomes. As a result of the present study, potential therapeutic targets for CAD were identified through bioinformatics analysis.

Indexed as

Computational BiologyData MiningChromosome MappingCoronary Artery DiseaseGene Expression ProfilingGene Expression RegulationGene Regulatory NetworksHumansMicroRNAsMolecular Sequence AnnotationProtein Interaction MappingProtein Interaction MapsRNA, MessengerTranscriptomeMicroRNAsRNA, Messengercoronary artery diseasegene ontologymicroRNA

Identifiers

PMID30320387
PMCPMC6236289
OpenAlexW2896850068

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.