Evidence map›Paper›PMID 36699386›Full record

ArticleBioinformatics advances2022

miRspongeR 2.0: an enhanced R package for exploring miRNA sponge regulation.

Junpeng Zhang, Lin Liu, Wu Zhang, Xiaomei Li, Chunwen Zhao, Sijing Li, Jiuyong Li, Thuc Duy Le

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PubMed Full text at PMC Publisher
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Article in Bioinformatics advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Modeling ncRNA Synergistic Regulation in Cancer.Methods in molecular biology (Clifton, N.J.) · 2025
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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

8 authors.

Junpeng ZhangDepartment of Information and Electronic Engineering, School of Engineering, Dali University, Dali 671003, China.ORCID https://orcid.org/0000-0001-6127-9701
Lin LiuUniSA STEM, University of South Australia, Mawson Lakes, SA 5095, Australia.
Wu ZhangDepartment of Molecular Biology, School of Agriculture and Biological Sciences, Dali University, Dali 671003, China.
Xiaomei LiUniSA STEM, University of South Australia, Mawson Lakes, SA 5095, Australia.ORCID https://orcid.org/0000-0002-8870-3186
Chunwen ZhaoDepartment of Information and Electronic Engineering, School of Engineering, Dali University, Dali 671003, China.
Sijing LiDepartment of Information and Electronic Engineering, School of Engineering, Dali University, Dali 671003, China.
Jiuyong LiUniSA STEM, University of South Australia, Mawson Lakes, SA 5095, Australia.ORCID https://orcid.org/0000-0002-9023-1878
Thuc Duy LeUniSA STEM, University of South Australia, Mawson Lakes, SA 5095, Australia.ORCID https://orcid.org/0000-0002-9732-4313

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Summary: MicroRNA (miRNA) sponges influence the capability of miRNA-mediated gene silencing by competing for shared miRNA response elements and play significant roles in many physiological and pathological processes. It has been proved that computational or dry-lab approaches are useful to guide wet-lab experiments for uncovering miRNA sponge regulation. However, all of the existing tools only allow the analysis of miRNA sponge regulation regarding a group of samples, rather than the miRNA sponge regulation unique to individual samples. Furthermore, most existing tools do not allow parallel computing for the fast identification of miRNA sponge regulation. Here, we present an enhanced version of our R/Bioconductor package, miRspongeR 2.0. Compared with the original version introduced in 2019, this package extends the resolution of miRNA sponge regulation from the multi-sample level to the single-sample level. Moreover, it supports the identification of miRNA sponge networks using parallel computing, and the construction of sample-sample correlation networks. It also provides more computational methods to infer miRNA sponge regulation and expands the ground truth for validation. With these new features, we anticipate that miRspongeR 2.0 will further accelerate the research on miRNA sponges with higher resolution and more utilities. Availability and implementation: http://bioconductor.org/packages/miRspongeR/. Supplementary information: Supplementary data are available at

Identifiers

PMID36699386
PMCPMC9710667

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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.