Evidence map›Paper›PMID 27665594›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2016

STarMir Tools for Prediction of microRNA Binding Sites.

Shaveta Kanoria, William Rennie, Chaochun Liu, C Steven Carmack, Jun Lu, Ye Ding

Abstract read
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

25 citing papers in PubMed.

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  20. Upregulated miRNAs on theFrontiers in genetics · 2022
    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

6 authors.

Shaveta KanoriaWadsworth Center, New York State Department of Health, Center for Medical Science, 150 New Scotland Avenue, Albany, NY, 12208, USA.
William RennieWadsworth Center, New York State Department of Health, Center for Medical Science, 150 New Scotland Avenue, Albany, NY, 12208, USA.
Chaochun LiuWadsworth Center, New York State Department of Health, Center for Medical Science, 150 New Scotland Avenue, Albany, NY, 12208, USA.
C Steven CarmackWadsworth Center, New York State Department of Health, Center for Medical Science, 150 New Scotland Avenue, Albany, NY, 12208, USA.
Jun LuDepartment of Genetics and Yale Stem Cell Center, Yale University, New Haven, CT, 06520, USA.
Ye DingWadsworth Center, New York State Department of Health, Center for Medical Science, 150 New Scotland Avenue, Albany, NY, 12208, USA. ye.ding@health.ny.gov.

Funding

Novel Approaches to Mammalian MicroRNA Target PredictionR01GM099811 · NIGMS · WADSWORTH CENTER · PI DING, YE, LU, JUN · 2012 to 2015
$2.4M
Quantitative Modeling of MicroRNA:Target Interactions in Cell Fate TransitionR01GM116855 · NIGMS · WADSWORTH CENTER · PI DING, YE, LU, JUN · 2016 to 2019
$2.2M
NIGMS NIH HHS R01 GM099811NIGMS NIH HHS R01 GM116855
6 · The paper itself

Abstract

MicroRNAs (miRNAs) are a class of endogenous short noncoding RNAs that regulate gene expression by targeting messenger RNAs (mRNAs), which results in translational repression and/or mRNA degradation. As regulatory molecules, miRNAs are involved in many mammalian biological processes and also in the manifestation of certain human diseases. As miRNAs play central role in the regulation of gene expression, understanding miRNA-binding patterns is essential to gain an insight of miRNA mediated gene regulation and also holds promise for therapeutic applications. Computational prediction of miRNA binding sites on target mRNAs facilitates experimental investigation of miRNA functions. This chapter provides protocols for using the STarMir web server for improved predictions of miRNA binding sites on a target mRNA. As an application module of the Sfold RNA package, the current version of STarMir is an implementation of logistic prediction models developed with high-throughput miRNA binding data from cross-linking immunoprecipitation (CLIP) studies. The models incorporated comprehensive thermodynamic, structural, and sequence features, and were found to make improved predictions of both seed and seedless sites, in comparison to the established algorithms (Liu et al., Nucleic Acids Res 41:e138, 2013). Their broad applicability was indicated by their good performance in cross-species validation. STarMir is freely available at http://sfold.wadsworth.org/starmir.html .

Indexed as

Base PairingBinding SitesSoftwareComputational BiologyMicroRNAsNucleic Acid ConformationRNA FoldingRNA, MessengerUser-Computer InterfaceWeb BrowserMicroRNAsRNA, MessengerCLIPmiRNAmiRNA binding siteRNA secondary structureTarget mRNA

Identifiers

PMID27665594
PMCPMC5353976

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.