Evidence map›Paper›PMID 28134831›Full record

ArticleInternational journal of molecular sciences2017

SpidermiR: An R/Bioconductor Package for Integrative Analysis with miRNA Data.

Claudia Cava, Antonio Colaprico, Gloria Bertoli, Alex Graudenzi, Tiago C Silva, Catharina Olsen, Houtan Noushmehr, Gianluca Bontempi, Giancarlo Mauri, Isabella Castiglioni

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing 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

35 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

10 authors.

Claudia CavaInstitute of Molecular Bioimaging and Physiology National Research Council (IBFM-CNR), Segrate (Mi) 20090, Italy. claudia.cava@ibfm.cnr.it.
Antonio ColapricoInteruniversity Institute of Bioinformatics in Brussels (IB)2, Brussels 1050, Belgium. antonio.colaprico@ulb.ac.be.
Gloria BertoliInstitute of Molecular Bioimaging and Physiology National Research Council (IBFM-CNR), Segrate (Mi) 20090, Italy. gloria.bertoli@ibfm.cnr.it.
Alex GraudenziInstitute of Molecular Bioimaging and Physiology National Research Council (IBFM-CNR), Segrate (Mi) 20090, Italy. alex.graudenzi@unimib.it.
Tiago C SilvaDepartment of Genetics Ribeirao Preto Medical School, University of Sao Paulo, Ribeirao Preto, Sao Paulo 14049-900, Brazil. tiagochst@gmail.com.
Catharina OlsenInteruniversity Institute of Bioinformatics in Brussels (IB)2, Brussels 1050, Belgium. colsen@ulb.ac.be.
Houtan NoushmehrDepartment of Genetics Ribeirao Preto Medical School, University of Sao Paulo, Ribeirao Preto, Sao Paulo 14049-900, Brazil. houtana@gmail.com.
Gianluca BontempiInteruniversity Institute of Bioinformatics in Brussels (IB)2, Brussels 1050, Belgium. gbonte@ulb.ac.be.
Giancarlo MauriDepartment of Informatics, Systems and Communication, University of Milan-Bicocca, Milan 20125, Italy. mauri@disco.unimib.it.
Isabella CastiglioniInstitute of Molecular Bioimaging and Physiology National Research Council (IBFM-CNR), Segrate (Mi) 20090, Italy. isabella.castiglioni@ibfm.cnr.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gene Regulatory Networks (GRNs) control many biological systems, but how such network coordination is shaped is still unknown. GRNs can be subdivided into basic connections that describe how the network members interact e.g., co-expression, physical interaction, co-localization, genetic influence, pathways, and shared protein domains. The important regulatory mechanisms of these networks involve miRNAs. We developed an R/Bioconductor package, namely SpidermiR, which offers an easy access to both GRNs and miRNAs to the end user, and integrates this information with differentially expressed genes obtained from The Cancer Genome Atlas. Specifically, SpidermiR allows the users to: (i) query and download GRNs and miRNAs from validated and predicted repositories; (ii) integrate miRNAs with GRNs in order to obtain miRNA-gene-gene and miRNA-protein-protein interactions, and to analyze miRNA GRNs in order to identify miRNA-gene communities; and (iii) graphically visualize the results of the analyses. These analyses can be performed through a single interface and without the need for any downloads. The full data sets are then rapidly integrated and processed locally.

Indexed as

SoftwareStatistics as TopicBreast NeoplasmsFemaleHumansMaleMicroRNAsNeoplasm ProteinsProstatic NeoplasmsProtein BindingMicroRNAsNeoplasm ProteinsgenemicroRNAnetworkprotein

Identifiers

PMID28134831
PMCPMC5343810

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.