Evidence map›Paper›PMID 31077152›Full record

ArticleBMC bioinformatics2019

miRspongeR: an R/Bioconductor package for the identification and analysis of miRNA sponge interaction networks and modules.

Junpeng Zhang, Lin Liu, Taosheng Xu, Yong Xie, Chunwen Zhao, Jiuyong Li, Thuc Duy Le

Abstract read
In one paragraph

Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

  1. Article
  2. Review
  3. Modeling ncRNA Synergistic Regulation in Cancer.Methods in molecular biology (Clifton, N.J.) · 2025
    Review
  4. Article
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  7. Article
  8. Article
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  17. Illuminating lncRNA Function Through Target Prediction.Methods in molecular biology (Clifton, N.J.) · 2021
    Article
  18. Review
  19. Review
  20. Review
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.

Junpeng ZhangSchool of Engineering, Dali University, Dali, 671003, Yunnan, China. zhangjunpeng_411@yahoo.com.ORCID http://orcid.org/0000-0001-6127-9701
Lin LiuSchool of Information Technology and Mathematical Sciences, University of South Australia, Mawson Lakes, SA, 5095, Australia.
Taosheng XuInstitute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, 230031, China.
Yong XieSchool of Engineering, Dali University, Dali, 671003, Yunnan, China.
Chunwen ZhaoSchool of Engineering, Dali University, Dali, 671003, Yunnan, China.
Jiuyong LiSchool of Information Technology and Mathematical Sciences, University of South Australia, Mawson Lakes, SA, 5095, Australia.
Thuc Duy LeSchool of Information Technology and Mathematical Sciences, University of South Australia, Mawson Lakes, SA, 5095, Australia. thuc.le@unisa.edu.au.

Funding

Applied Basic Research Foundation of Yunnan Province 2017FB099Australian Research Council Discovery Grant DP140103617National Health and Medical Research Council 1123042National Natural Science Foundation of China 61702069
6 · The paper itself

Abstract

backgroundA microRNA (miRNA) sponge is an RNA molecule with multiple tandem miRNA response elements that can sequester miRNAs from their target mRNAs. Despite growing appreciation of the importance of miRNA sponges, our knowledge of their complex functions remains limited. Moreover, there is still a lack of miRNA sponge research tools that help researchers to quickly compare their proposed methods with other methods, apply existing methods to new datasets, or select appropriate methods for assisting in subsequent experimental design.

resultsTo fill the gap, we present an R/Bioconductor package, miRspongeR, for simplifying the procedure of identifying and analyzing miRNA sponge interaction networks and modules. It provides seven popular methods and an integrative method to identify miRNA sponge interactions. Moreover, it supports the validation of miRNA sponge interactions and the identification of miRNA sponge modules, as well as functional enrichment and survival analysis of miRNA sponge modules.

conclusionsThis package enables researchers to quickly evaluate their new methods, apply existing methods to new datasets, and consequently speed up miRNA sponge research.

Indexed as

Gene Regulatory NetworksHumansMicroRNAsMicroRNAsceRNAHuman breast invasive carcinomamiRNAmiRNA spongemiRNA sponge interaction networksmiRNA sponge modules

Identifiers

PMID31077152
PMCPMC6509829

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Registered trials

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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.