Evidence map›Paper›PMID 30003085›Full record

ArticleInternational journal of genomics2018

Nonredundant, Highly Connected MicroRNAs Control Functionality in Breast Cancer Networks.

Guillermo de Anda-Jáuregui, Jesús Espinal-Enríquez, Diana Drago-García, Enrique Hernández-Lemus

Open access · goldAbstract read
In one paragraph

Article in International journal of genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
1.5field-weighted citation impact, top 18% 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

17 citing papers in PubMed, 24 citations in OpenAlex.

  1. Loss of long-range co-expression is a common feature in cancer.NPJ systems biology and applications · 2026
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  16. The Regulatory Role of MicroRNAs in Breast Cancer.International journal of molecular sciences · 2019
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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

4 authors at 3 institutions in 2 countries.

Guillermo de Anda-JáureguiComputational Genomics Division, National Institute of Genomic Medicine, 14610 Mexico City, Mexico.
Jesús Espinal-EnríquezComputational Genomics Division, National Institute of Genomic Medicine, 14610 Mexico City, Mexico.
Diana Drago-GarcíaDepartment of Biological Regulation, Weizmann Institute of Science, 7610001 Rehovot, Israel.
Enrique Hernández-LemusComputational Genomics Division, National Institute of Genomic Medicine, 14610 Mexico City, Mexico.ORCID 0000-0002-1872-1397
Universidad Autónoma de la Ciudad de México · MXNational Institute of Genomic Medicine · MXWeizmann Institute of Science · IL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alterations to transcriptional regulation are an important factor in breast cancer. Noncoding RNA, such as microRNA (miR), have very influential roles in the transcriptional regulation of genes. Transcriptional regulation can be successfully modeled and analyzed using complex network theory. Particularly, interactions between two distinct classes of biological elements, such as miR and genes, can be approached through the bipartite network formalism. Based on bipartite network properties, it is possible to identify highly influential miRs in the network, such as those that have a large number of connections indicating regulation of a large set of genes. Some miRs in a network are nonredundant, which indicates that they are solely responsible of the regulation of a particular set of genes, which in turn may be associated to a particular biological process. We hypothesize that highly influential, nonredundant miRs, which we call

Identifiers

PMID30003085
PMCPMC5996465
OpenAlexW2806254489

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.