Evidence map›Paper›PMID 32631332›Full record

ArticleBMC bioinformatics2020

MMiRNA-Viewer

Yongsheng Bai, Steve Baker, Kevin Exoo, Xingqin Dai, Lizhong Ding, Naureen Aslam Khattak, Hongtao Li, Hannah Liu, Xiaoming Liu

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC bioinformatics, 2020. 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 57% 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. Biclustering data analysis: a comprehensive survey.Briefings in bioinformatics · 2024
    Review
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 4 institutions in 1 country.

Yongsheng BaiDepartment of Biology, Indiana State University, Terre Haute, IN, 47809, USA. yongshengbaicool@gmail.com.ORCID http://orcid.org/0000-0002-9944-5426
Steve BakerDepartment of Mathematics and Computer Science, Indiana State University, Terre Haute, IN, 47809, USA.
Kevin ExooDepartment of Mathematics and Computer Science, Indiana State University, Terre Haute, IN, 47809, USA.
Xingqin DaiDepartment of Mathematics and Computer Science, Indiana State University, Terre Haute, IN, 47809, USA.
Lizhong DingDepartment of Biology, Indiana State University, Terre Haute, IN, 47809, USA.
Naureen Aslam KhattakDepartment of Biology, Indiana State University, Terre Haute, IN, 47809, USA.
Hongtao LiDepartment of Science and Mathematics, St Mary-of-the-Woods College, Saint Mary of the Woods, IN, 47876, USA.
Hannah LiuCarmel High School, 520 E. Main St., Carmel, IN, 46032, USA.
Xiaoming LiuUSF Genomics, College of Public Health, University of South Florida, Tampa, FL, 33620, USA.
Indiana State University · USSaint Mary-of-the-Woods College · USUniversity of Michigan · USUniversity of South Florida · US

Funding

Indiana Academy of Sciences NAIndiana State University NAUniversity of South Florida NA
6 · The paper itself

Abstract

backgroundAlthough there are many studies on the characteristics of miRNA-mRNA interactions using miRNA and mRNA sequencing data, the complexity of the change of the correlation coefficients and expression values of the miRNA-mRNA pairs between tumor and normal samples is still not resolved, and this hinders the potential clinical applications. There is an urgent need to develop innovative methodologies and tools that can characterize and visualize functional consequences of cancer risk gene and miRNA pairs while analyzing the tumor and normal samples simultaneously.

resultsWe developed an innovative bioinformatics tool for visualizing functional annotation of miRNA-mRNA pairs in a network, known as MMiRNA-Viewer

conclusionOur MMiRNA-Viewer

Indexed as

Computational BiologyHumansMicroRNAsRNA, MessengerMicroRNAsRNA, MessengerClustering algorithmGene regulationmiRNAMMiRNA-Viewer2mRNATarget predictionThe cancer genome atlasVisualization

Identifiers

PMID32631332
PMCPMC7336395
OpenAlexW3038875664

What OpenQuestion 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 OpenQuestion graph.