Evidence map›Paper›PMID 36299582›Full record

ArticleFrontiers in genetics2022

Bioinformatics analysis to screen for genes related to myocardial infarction.

Liting Yang, Xuyang Pan, Ying Zhang, Dongsheng Zhao, Liang Wang, Guoliang Yuan, Changgao Zhou, Tao Li, Wei Li

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
3.6field-weighted citation impact, top 6% 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

32 citing papers in PubMed, 26 citations in OpenAlex.

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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

9 authors at 1 institution in 1 country.

Liting YangDepartment of Cardiology, Shuyang Hospital of Traditional Chinese Medicine, Suqian, Jiangsu, China.
Xuyang PanDepartment of Cardiology, Shuyang Hospital of Traditional Chinese Medicine, Suqian, Jiangsu, China.
Ying ZhangDepartment of Cardiology, Shuyang Hospital of Traditional Chinese Medicine, Suqian, Jiangsu, China.
Dongsheng ZhaoDepartment of Cardiology, Shuyang Hospital of Traditional Chinese Medicine, Suqian, Jiangsu, China.
Liang WangDepartment of Cardiology, Shuyang Hospital of Traditional Chinese Medicine, Suqian, Jiangsu, China.
Guoliang YuanDepartment of Cardiology, Shuyang Hospital of Traditional Chinese Medicine, Suqian, Jiangsu, China.
Changgao ZhouDepartment of Cardiology, Shuyang Hospital of Traditional Chinese Medicine, Suqian, Jiangsu, China.
Tao LiDepartment of Cardiology, Shuyang Hospital of Traditional Chinese Medicine, Suqian, Jiangsu, China.
Wei LiDepartment of Cardiology, Shuyang Hospital of Traditional Chinese Medicine, Suqian, Jiangsu, China.
Anyang Hospital of Traditional Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Myocardial infarction (MI) is an acute and persistent myocardial ischemia caused by coronary artery disease. This study screened potential genes related to MI. Three gene expression datasets related to MI were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened using the MetaDE package. Afterward, the modules and genes closely related to MI were screened and a gene co-expression network was constructed. A support vector machine (SVM) classification model was then constructed based on the GSE61145 dataset using the e1071 package in R. A total of 98 DEGs were identified in the MI samples. Next, three modules associated with MI were screened and an SVM classification model involving seven genes was constructed. Among them,

Indexed as

differentially expressed genesgene co-expression networkmyocardial infarctionsupport vector machineweighed gene co-expression network analysis

Identifiers

PMID36299582
PMCPMC9589498
OpenAlexW4303980212

What Socratic 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 Socratic graph.