Evidence map›Paper›PMID 32484539›Full record

ArticleNucleic acids research2020

miRNet 2.0: network-based visual analytics for miRNA functional analysis and systems biology.

Le Chang, Guangyan Zhou, Othman Soufan, Jianguo Xia

Abstract read
In one paragraph

Article in Nucleic acids research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 536 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
536citing papers in PubMed, 2 pooled it
–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

536 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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476 more citing papers are in PubMed but not listed here.

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.

Le ChangDepartment of Human Genetics, McGill University, Montreal, Quebec, Canada.
Guangyan ZhouInstitute of Parasitology, McGill University, Montreal, Quebec, Canada.
Othman SoufanInstitute of Parasitology, McGill University, Montreal, Quebec, Canada.
Jianguo XiaDepartment of Human Genetics, McGill University, Montreal, Quebec, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

miRNet is an easy-to-use, web-based platform designed to help elucidate microRNA (miRNA) functions by integrating users' data with existing knowledge via network-based visual analytics. Since its first release in 2016, miRNet has been accessed by >20 000 researchers worldwide, with ∼100 users on a daily basis. While version 1.0 was focused primarily on miRNA-target gene interactions, it has become clear that in order to obtain a global view of miRNA functions, it is necessary to bring other important players into the context during analysis. Driven by this concept, in miRNet version 2.0, we have (i) added support for transcription factors (TFs) and single nucleotide polymorphisms (SNPs) that affect miRNAs, miRNA-binding sites or target genes, whilst also greatly increased (>5-fold) the underlying knowledgebases of miRNAs, ncRNAs and disease associations; (ii) implemented new functions to allow creation and visual exploration of multipartite networks, with enhanced support for in situ functional analysis and (iii) revamped the web interface, optimized the workflow, and introduced microservices and web application programming interface (API) to sustain high-performance, real-time data analysis. The underlying R package is also released in tandem with version 2.0 to allow more flexible data analysis for R programmers. The miRNet 2.0 website is freely available at https://www.mirnet.ca.

Indexed as

Gene Regulatory NetworksSoftwareComputer GraphicsGene Expression RegulationHumansKnowledge BasesMicroRNAsMultiple SclerosisPolymorphism, Single NucleotideSystems BiologyTranscription FactorsMicroRNAsTranscription Factors

Identifiers

PMID32484539
PMCPMC7319552

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.