Evidence map›Paper›PMID 32227657›Full record

ArticleHuman mutation2020

dbMTS: A comprehensive database of putative human microRNA target site SNVs and their functional predictions.

Chang Li, Chengcheng Mou, Michael D Swartz, Bing Yu, Yongsheng Bai, Yicheng Tu, Xiaoming Liu

Abstract read
In one paragraph

Article in Human mutation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 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

7 authors.

Chang LiUSF Genomics, College of Public Health, University of South Florida, Tampa, Florida.
Chengcheng MouDepartment of Computer Science and Engineering, College of Engineering, University of South Florida, Tampa, Florida.
Michael D SwartzDepartment of Biostatistics, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas.
Bing YuDepartment of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas.
Yongsheng BaiDepartment of Internal Medicine, University of Michigan, Ann Arbor, Michigan.
Yicheng TuDepartment of Computer Science and Engineering, College of Engineering, University of South Florida, Tampa, Florida.
Xiaoming LiuUSF Genomics, College of Public Health, University of South Florida, Tampa, Florida.ORCID 0000-0001-8285-5528

Funding

Genomic Architecture of Common Disease in Diverse Populations: WGS of Ongoing Hemorrhagic Stroke Study SupplementUM1HG008898 · NHGRI · BAYLOR COLLEGE OF MEDICINE · PI GIBBS, RICHARD A · 2016 to 2020
$77.0M
NHGRI NIH HHS UM1 HG008898
6 · The paper itself

Abstract

MicroRNAs (miRNA) are short noncoding RNAs that can repress the expression of protein-coding messenger RNAs (mRNAs) by binding to the 3'-untranslated region (UTR) of the target. Genetic mutations such as single nucleotide variants (SNVs) in the 3'-UTR of the mRNAs can disrupt miRNA regulation. In this study, we presented dbMTS, a database for miRNA target site (MTS) SNVs and their functional annotations. This database can help studies easily identify putative SNVs that affect miRNA targeting and facilitate the prioritization of their functional importance. dbMTS is freely available for academic use at http://database.liulab.science/dbMTS as a web service or a downloadable attached database of dbNSFP.

Indexed as

Databases, GeneticMicroRNAsPolymorphism, Single Nucleotide3' Untranslated RegionsComputational BiologyHumansInternetSoftware3' Untranslated RegionsMicroRNAs3′-untranslated regiondatabasefunctional predictionmicroRNA targetvariant

Identifiers

PMID32227657
PMCPMC7251985

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.