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Related Concept Videos

MicroRNAs01:22

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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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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 the pre-miRNA...
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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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RNA Interference01:23

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RNA interference (RNAi) is a process in which a small non-coding RNA molecule blocks the post-transcriptional expression of a gene by binding to its messenger RNA (mRNA) and preventing the protein from being translated.
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Small interfering RNAs, or siRNAs, are short regulatory RNA molecules that can silence genes post-transcriptionally, as well as the transcriptional level in some cases. siRNAs are important for protecting cells against viral infections and silencing transposable genetic elements.
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Related Experiment Video

Updated: Oct 26, 2025

In Vivo Nanovector Delivery of a Heart-specific MicroRNA-sponge
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In Vivo Nanovector Delivery of a Heart-specific MicroRNA-sponge

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Time to infer miRNA sponge modules.

Junpeng Zhang1,2, Lin Liu3, Taosheng Xu4

  • 1Center for Informational Biology, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.

Wiley Interdisciplinary Reviews. RNA
|August 3, 2021
PubMed
Summary
This summary is machine-generated.

Discovering competing endogenous RNA (ceRNA) or microRNA (miRNA) sponge modules is crucial for understanding biological processes and diseases. This review highlights computational methods for identifying these modules using heterogeneous data, aiding in disease mechanism discovery.

Keywords:
ceRNAgene co-expression modulehuman cancermiRNAmiRNA sponge module

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Area of Science:

  • RNA Biology
  • Computational Biology
  • Genomics

Background:

  • Competing endogenous RNA (ceRNA) networks regulate gene expression through microRNA (miRNA) sponging.
  • Identifying functional miRNA sponge modules is essential for understanding complex biological processes and diseases.

Purpose of the Study:

  • To provide a comprehensive overview of methods for discovering miRNA sponge modules.
  • To review databases and computational approaches for ceRNA module inference.

Main Methods:

  • Literature review of publicly available cancer-related miRNA sponge databases.
  • Review of existing computational methods for inferring miRNA sponge modules.
  • Performance assessment of module discovery methods using pan-cancer datasets.

Main Results:

  • Heterogeneous data mapping directly to competitive modules aids in inferring biologically meaningful miRNA sponge modules.
  • Cancer-related miRNA sponges are key to discovering cancer-associated modules.
  • Computational methods offer a novel approach to discerning competitive effects of miRNA sponges in complex diseases.

Conclusions:

  • The direct mapping of heterogeneous data to competitive modules is effective for inferring biologically significant miRNA sponge modules.
  • Further development of in silico methods is needed to address challenges in miRNA sponge module inference.
  • This work provides a perspective on current and future directions in computational ceRNA module discovery.