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Related Concept Videos

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MicroRNA (miRNA) are short, regulatory RNA transcribed from introns—non-coding regions of a gene—or intergenic regions—stretches of DNA present between genes. Several processing steps are required to form biologically active, mature miRNA. The initial transcript, called primary miRNA (pri-mRNA), base-pairs with itself forming a stem-loop structure. Within the nucleus, an endonuclease enzyme, called Drosha, shortens the stem-loop structure into hairpin-shaped pre-miRNA. After...
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RNA interference (RNAi) is a cellular mechanism that inhibits gene expression by suppressing its transcription or activating the RNA degradation process. The mechanism was discovered by Andrew Fire and Craig Mello in 1998 in plants. Today, it is observed in almost all eukaryotes, including protozoa, flies, nematodes, insects, parasites, and mammals. This precise cellular mechanism of gene silencing has been developed into a technique that provides an efficient way to identify and determine the...
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PIWI-interacting RNAs, or piRNAs, are the most abundant short non-coding RNAs. More than 20,000 genes have been found in humans that code for piRNAs while only 2000 genes have been found for miRNAs. piRNAs can act at the transcriptional and post-transcriptional levels and have a vital role in silencing transposable elements present in germ cells. They are also involved in epigenetic silencing and activation. Previously, they were thought to function only in germ cells but new evidence suggests...
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miRspongeR 2.0: an enhanced R package for exploring miRNA sponge regulation.

Junpeng Zhang1, Lin Liu2, Wu Zhang3

  • 1Department of Information and Electronic Engineering, School of Engineering, Dali University, Dali 671003, China.

Bioinformatics Advances
|January 26, 2023
PubMed
Summary
This summary is machine-generated.

The miRspongeR 2.0 package enables single-sample microRNA (miRNA) sponge analysis and parallel computing for faster identification of miRNA sponge networks, advancing research in gene regulation.

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Area of Science:

  • Computational biology
  • Genomics
  • Molecular biology

Background:

  • MicroRNA (miRNA) sponges regulate gene silencing by competing for miRNA response elements.
  • Existing computational tools analyze miRNA sponge regulation at a group level, not for individual samples.
  • Current tools lack parallel computing for efficient miRNA sponge identification.

Purpose of the Study:

  • To introduce miRspongeR 2.0, an enhanced R/Bioconductor package for miRNA sponge analysis.
  • To extend miRNA sponge regulation analysis to the single-sample level.
  • To enable parallel computing for faster identification of miRNA sponge networks.

Main Methods:

  • Development of miRspongeR 2.0, an updated R/Bioconductor package.
  • Implementation of single-sample level analysis for miRNA sponge regulation.
  • Integration of parallel computing for accelerated network identification.
  • Inclusion of additional computational methods and expanded ground truth for validation.

Main Results:

  • miRspongeR 2.0 provides single-sample resolution for miRNA sponge regulation analysis.
  • The package supports parallel computing for rapid identification of miRNA sponge networks.
  • New computational methods and validation resources are incorporated.

Conclusions:

  • miRspongeR 2.0 enhances the study of miRNA sponges with single-sample resolution.
  • The package accelerates research through efficient, high-resolution analysis of miRNA sponge networks.