Evidence map›Paper›PMID 27689084›Full record

ArticleBioMed research international

Analyzing the miRNA-Gene Networks to Mine the Important miRNAs under Skin of Human and Mouse.

Jianghong Wu, Husile Gong, Yongsheng Bai, Wenguang Zhang

Open access · hybridAbstract read
In one paragraph

Article in BioMed research international. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 28% 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

3 citing papers in PubMed, 6 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

4 authors at 2 institutions in 2 countries.

Jianghong WuCollege of Animal Science, Inner Mongolia Agricultural University, Hohhot 010018, China; Inner Mongolia Academy of Agricultural & Animal Husbandry Sciences, Hohhot 010031, China; Inner Mongolia Prataculture Research Center, Chinese Academy of Science, Hohhot 010031, China; State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Department of Biology, Indiana State University, Terre Haute, IN 47809, USA.ORCID 0000-0003-4027-2345
Husile GongCollege of Animal Science, Inner Mongolia Agricultural University, Hohhot 010018, China; Inner Mongolia Academy of Agricultural & Animal Husbandry Sciences, Hohhot 010031, China.
Yongsheng BaiDepartment of Biology, Indiana State University, Terre Haute, IN 47809, USA; The Center for Genomic Advocacy, Indiana State University, Terre Haute, IN 47809, USA.ORCID 0000-0002-9944-5426
Wenguang ZhangCollege of Animal Science, Inner Mongolia Agricultural University, Hohhot 010018, China.ORCID 0000-0002-3508-588X
Inner Mongolia Agricultural University · CNIndiana State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genetic networks provide new mechanistic insights into the diversity of species morphology. In this study, we have integrated the MGI, GEO, and miRNA database to analyze the genetic regulatory networks under morphology difference of integument of humans and mice. We found that the gene expression network in the skin is highly divergent between human and mouse. The GO term of secretion was highly enriched, and this category was specific in human compared to mouse. These secretion genes might be involved in eccrine system evolution in human. In addition, total 62,637 miRNA binding target sites were predicted in human integument genes (IGs), while 26,280 miRNA binding target sites were predicted in mouse IGs. The interactions between miRNAs and IGs in human are more complex than those in mouse. Furthermore,

Identifiers

PMID27689084
PMCPMC5027296
OpenAlexW2513744133

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.