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Related Concept Videos

MicroRNAs01:22

MicroRNAs

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...
MicroRNAs01:22

MicroRNAs

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 ends...
MicroRNAs01:22

MicroRNAs

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 ends...
siRNA - Small Interfering RNAs02:30

siRNA - Small Interfering RNAs

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.
In the cytoplasm, siRNA is processed from a double-stranded RNA, which comes from either endogenous DNA transcription or exogenous sources like a virus. This double-stranded RNA is then cleaved by the ATP-dependent...

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Updated: Jun 17, 2026

Detection of miRNA Targets in High-throughput Using the 3'LIFE Assay
12:49

Detection of miRNA Targets in High-throughput Using the 3'LIFE Assay

Published on: May 25, 2015

Computational methods to identify miRNA targets.

Molly Hammell1

  • 1Program in Molecular Medicine, University of Massachusetts Medical School, 373 Plantation Street, Biotech II, Suite 306, Worcester, MA 01605, USA. molly.hammell@umassmed.edu

Seminars in Cell & Developmental Biology
|January 19, 2010
PubMed
Summary
This summary is machine-generated.

MicroRNAs (miRNAs) regulate gene expression, but their precise roles are unclear. This review compares computational tools for identifying miRNA targets, focusing on methods validated by experimental data.

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Related Experiment Videos

Last Updated: Jun 17, 2026

Detection of miRNA Targets in High-throughput Using the 3'LIFE Assay
12:49

Detection of miRNA Targets in High-throughput Using the 3'LIFE Assay

Published on: May 25, 2015

Genome-wide Screen for miRNA Targets Using the MISSION Target ID Library
08:40

Genome-wide Screen for miRNA Targets Using the MISSION Target ID Library

Published on: April 6, 2012

Biotin-based Pulldown Assay to Validate mRNA Targets of Cellular miRNAs
11:00

Biotin-based Pulldown Assay to Validate mRNA Targets of Cellular miRNAs

Published on: June 12, 2018

Area of Science:

  • Molecular Biology
  • Genetics
  • Bioinformatics

Background:

  • MicroRNAs (miRNAs) are key regulators of gene expression at the post-transcriptional level.
  • The precise mechanisms and outcomes of miRNA-mediated gene regulation are not fully understood.
  • Accurate identification of miRNA targets is crucial for understanding their roles in gene regulatory networks.

Purpose of the Study:

  • To review and compare computational methods for predicting miRNA targets in animals.
  • To emphasize approaches that integrate experimental validation of miRNA:target interactions.

Main Methods:

  • Comparative analysis of existing computational miRNA target prediction algorithms.
  • Focus on methods incorporating experimental data, such as those analyzing miRNA:target complexes.

Main Results:

  • Computational methods for miRNA target prediction vary significantly in their accuracy, scope, and usability.
  • Experimental validation is essential for refining prediction accuracy and understanding miRNA function.
  • A growing number of tools are available, but their performance and applicability differ.

Conclusions:

  • Accurate miRNA target prediction is vital for advancing our understanding of gene regulation.
  • Integrating computational predictions with experimental evidence is the most robust approach.
  • Further development and validation of prediction tools are needed to fully elucidate miRNA functions.